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The returned object contains now additionally + * the rank of the input matrix, the original eigenvalues (of all variables) + * and the original total variance, if available. + +2021-09-15 Valentin Todorov * * DESCRIPTION (Version): 1.6-0 * * R/PcaHubert.R - option for adjusted outlyingness for skewed data added * data/machines.rda - data set Computer Hardware added - * Fixed some URLs, particularly the reference to https.javasoft.org + * data/wolves.rda - data set 'wolves' added + * Fixed some URLs, particularly the reference to javasoft.org 2020-08-03 Valentin Todorov * Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/Appalachia.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/Appalachia.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/bushmiss.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/bushmiss.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/bus.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/bus.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/Cascades.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/Cascades.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/diabetes.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/diabetes.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/fish.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/fish.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/fruit.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/fruit.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/hemophilia.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/hemophilia.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/lmom32.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/lmom32.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/lmom33.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/lmom33.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/machines.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/machines.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/maryo.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/maryo.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/octane.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/octane.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/olitos.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/olitos.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/OsloTransect.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/OsloTransect.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/pottery.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/pottery.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/rice.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/rice.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/salmon.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/salmon.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/soil.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/soil.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/un86.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/un86.rda differ Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/data/wages.rda and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/data/wages.rda differ diff -Nru r-cran-rrcov-1.6-0/debian/changelog r-cran-rrcov-1.6-2/debian/changelog --- r-cran-rrcov-1.6-0/debian/changelog 2021-09-21 09:44:03.000000000 +0000 +++ r-cran-rrcov-1.6-2/debian/changelog 2022-02-13 07:11:37.000000000 +0000 @@ -1,3 +1,14 @@ +r-cran-rrcov (1.6-2-1) unstable; urgency=medium + + * Team upload + * New upstream version + * Disable reprotest + * dh-update-R to update Build-Depends (routine-update) + * Set upstream metadata fields: Bug-Database, Bug-Submit, Repository, + Repository-Browse. + + -- Andreas Tille Sun, 13 Feb 2022 08:11:37 +0100 + r-cran-rrcov (1.6-0-1) unstable; urgency=medium * Team upload. diff -Nru r-cran-rrcov-1.6-0/debian/control r-cran-rrcov-1.6-2/debian/control --- r-cran-rrcov-1.6-0/debian/control 2021-09-21 09:44:03.000000000 +0000 +++ r-cran-rrcov-1.6-2/debian/control 2022-02-13 07:11:37.000000000 +0000 @@ -7,7 +7,7 @@ Build-Depends: debhelper-compat (= 13), dh-r, r-base-dev, - r-cran-robustbase (>= 0.92.1), + r-cran-robustbase, r-cran-mvtnorm, r-cran-lattice, r-cran-pcapp diff -Nru r-cran-rrcov-1.6-0/debian/salsa-ci.yml r-cran-rrcov-1.6-2/debian/salsa-ci.yml --- r-cran-rrcov-1.6-0/debian/salsa-ci.yml 2021-09-21 09:44:03.000000000 +0000 +++ r-cran-rrcov-1.6-2/debian/salsa-ci.yml 2022-02-13 07:11:37.000000000 +0000 @@ -3,9 +3,9 @@ - https://salsa.debian.org/salsa-ci-team/pipeline/raw/master/salsa-ci.yml - https://salsa.debian.org/salsa-ci-team/pipeline/raw/master/pipeline-jobs.yml + # R creates .rdb files and .rds with some randomness. # https://tests.reproducible-builds.org/debian/issues/unstable/randomness_in_r_rdb_rds_databases_issue.html -# Uncomment the following two lines if this package is affected. -#variables: -# SALSA_CI_DISABLE_REPROTEST: 1 - +# Thus reprotest is disabled here +variables: + SALSA_CI_DISABLE_REPROTEST: 1 diff -Nru r-cran-rrcov-1.6-0/debian/upstream/metadata r-cran-rrcov-1.6-2/debian/upstream/metadata --- r-cran-rrcov-1.6-0/debian/upstream/metadata 2021-09-21 09:44:03.000000000 +0000 +++ r-cran-rrcov-1.6-2/debian/upstream/metadata 2022-02-13 07:11:37.000000000 +0000 @@ -1 +1,5 @@ Archive: CRAN +Bug-Database: https://github.com/valentint/rrcov/issues +Bug-Submit: https://github.com/valentint/rrcov/issues/new +Repository: https://github.com/valentint/rrcov.git +Repository-Browse: https://github.com/valentint/rrcov diff -Nru r-cran-rrcov-1.6-0/DESCRIPTION r-cran-rrcov-1.6-2/DESCRIPTION --- r-cran-rrcov-1.6-0/DESCRIPTION 2021-09-16 05:10:07.000000000 +0000 +++ r-cran-rrcov-1.6-2/DESCRIPTION 2022-02-10 12:20:02.000000000 +0000 @@ -1,7 +1,6 @@ Package: rrcov -Version: 1.6-0 -Date: 2021-08-27 -VersionNote: Released 1.5-5 on 2020-08-03 on CRAN +Version: 1.6-2 +VersionNote: Released 1.6-1 on 2022-01-28 on CRAN Title: Scalable Robust Estimators with High Breakdown Point Authors@R: c(person("Valentin", "Todorov", role = c("aut", "cre"), email = "valentin.todorov@chello.at", comment=c(ORCID = "0000-0003-4215-0245"))) Description: Robust Location and Scatter Estimation and Robust @@ -19,9 +18,11 @@ Suggests: grid, MASS LazyLoad: yes License: GPL (>= 3) +URL: https://github.com/valentint/rrcov +BugReports: https://github.com/valentint/rrcov/issues Repository: CRAN -Packaged: 2021-09-15 22:24:43 UTC; valen +Packaged: 2022-02-09 09:37:21 UTC; valen NeedsCompilation: yes Author: Valentin Todorov [aut, cre] () -Date/Publication: 2021-09-16 05:10:07 UTC -RoxygenNote: 7.1.1 +Date/Publication: 2022-02-10 12:20:02 UTC +RoxygenNote: 7.1.2 diff -Nru r-cran-rrcov-1.6-0/inst/Citation r-cran-rrcov-1.6-2/inst/Citation --- r-cran-rrcov-1.6-0/inst/Citation 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/inst/Citation 2022-01-21 20:48:39.000000000 +0000 @@ -1,6 +1,7 @@ citHeader("To cite rrcov in publications use:") -citEntry(entry = "Article", +citEntry( +entry = "Article", title = "An Object-Oriented Framework for Robust Multivariate Analysis", author = personList(as.person("Valentin Todorov"), as.person("Peter Filzmoser")), @@ -9,13 +10,12 @@ volume = "32", number = "3", pages = "1--47", - url = "https://www.jstatsoft.org/article/view/v032i03", - + doi = "10.18637/jss.v032.i03", textVersion = - paste("Valentin Todorov, Peter Filzmoser (2009).", - "An Object-Oriented Framework for Robust Multivariate Analysis.", - "Journal of Statistical Software, 32(3), 1-47.", - "URL https://www.jstatsoft.org/article/view/v032i03.") + paste("Valentin Todorov, Peter Filzmoser (2009).", + "An Object-Oriented Framework for Robust Multivariate Analysis.", + "Journal of Statistical Software, 32(3), 1-47.", + "DOI: 10.18637/jss.v032.i03.") ) Binary files /tmp/tmpg8h7q9sx/UAF50oGZx2/r-cran-rrcov-1.6-0/inst/doc/rrcov.pdf and /tmp/tmpg8h7q9sx/SeunafBUSy/r-cran-rrcov-1.6-2/inst/doc/rrcov.pdf differ diff -Nru r-cran-rrcov-1.6-0/inst/examples/ex-pca-explained-variance.R r-cran-rrcov-1.6-2/inst/examples/ex-pca-explained-variance.R --- r-cran-rrcov-1.6-0/inst/examples/ex-pca-explained-variance.R 1970-01-01 00:00:00.000000000 +0000 +++ r-cran-rrcov-1.6-2/inst/examples/ex-pca-explained-variance.R 2022-02-07 13:51:38.000000000 +0000 @@ -0,0 +1,62 @@ +## Showing correctly the percentage explained variance in PCA +## +## If not all PCA were extracted, which is a great advantage in +## the case in high dimensional data, the PCA methods in rrcov +## could not show correctly the percentage of variance explained, +## Because the total variance explained, i.e. the sum of _all_ +## eigenvalues was not known. Now this is fixed, differently in +## the different methods. + +## In PcaClassic, PcaCov and PcaLocantore, this is nt a problem +## because always all eigenvalues are computed. +## +## In PcaHubert there is a preliminary step in which the classical +## PCA are computed on the data set without outliers identified by +## the Stahel-Donoho Outlyingness. All eigenvalues are calculated +## and used for selecting the number of components and for +## presenting the percentage of explaned variance. +## +## In the pure projection purcuit methods PcaGrid() and PcaProj() +## this cannot be done and a note is written that the proportion +## of variance and cumulative proportion are not shown because the +## chosen number of components is smaller than the rank of the data +## matrix. + +library(rrcov) + +data(hbk) + +## PCA with all variables +(pca1 <- PcaHubert(hbk, k=ncol(hbk), trace=TRUE, mcd=TRUE, skew=FALSE)) +summary(pca1) + +## PCA with number of components selected by the algorithm +(pca2 <- PcaHubert(hbk, trace=TRUE, mcd=TRUE, skew=FALSE)) +summary(pca2) + +## PCA with number of components selected by the user +(pca3 <- PcaHubert(hbk, k=2, trace=TRUE, mcd=TRUE, skew=FALSE)) +summary(pca3) + +## PCA by the projection algorithm with number of components selected by the user. +## Here we cannot show the proportion of variance and the cumulative proportion +(pca4 <- PcaGrid(hbk, k=2, trace=TRUE)) +summary(pca4) + +## The other PCA methods available in rrcov +summary(PcaClassic(hbk, k=2)) +summary(PcaCov(hbk, k=2)) +summary(PcaLocantore(hbk, k=2)) +summary(PcaProj(hbk, k=2)) + +## Example with the newly added to 'rrcov' data set fruit ======== +data(fruit) +# Remove the first variable, the grouping one +(pca <- PcaHubert(fruit[,-1], trace=TRUE)) +summary(pca) + +screeplot(pca) + +(pca <- PcaHubert(fruit[,-1], k=4) +summapry(pca) +plot(pca) diff -Nru r-cran-rrcov-1.6-0/inst/examples/ex-pca-skew.R r-cran-rrcov-1.6-2/inst/examples/ex-pca-skew.R --- r-cran-rrcov-1.6-0/inst/examples/ex-pca-skew.R 1970-01-01 00:00:00.000000000 +0000 +++ r-cran-rrcov-1.6-2/inst/examples/ex-pca-skew.R 2022-02-06 16:02:47.000000000 +0000 @@ -0,0 +1,49 @@ +## PCA for skewed data +## +## The present robust PCA methods like ROBPCA work best if the +## non-outlying data have an approximately symmetric distribution. +## When the original variables are skewed, too many points tend +## to be flagged as outlying. Hubert et al. (2009) developed a +## robust method which is also suitable for skewed data. Also, the +## outlier map is modified to present adequately the PCA outliers. +## +## In PcaHubert() the version for skewed data is invoked using the +## argument skew=TRUE. Example with the computer hardware data +## follows + +library(rrcov) + +data(machines) +## The data set contains 209 observations, and 8 variables. + +## First we robustly center and scale the variables by subtracting +## the median and dividing by the median absolute deviation (MAD). +## Of course, this could be done also later, when calling the PCA +## function, by setting the arguments 'center' and 'sacle' to TRUE. +data <- robustbase::doScale(machines, center=median, scale=mad) +X <- data$x + +## Each of the variables is significantly skewed as measured by +## its medcouple. The corresponding p-values can be computed using +## the formulas in using the formulas in Brys et al. (2004). These +## show the variables are all significantly asymmetric. +data.frame(MC=round(apply(X, 2, mc),2)) + +## Plot a pairwise scaterplot matrix +mcd <- CovMcd(X[,1:6]) +plot(mcd, which="pairs") + +## Remove the rownames (too long) +rownames(X) <- NULL + +## Start with robust PCA based on MCD (P << n) +(pca1 <- PcaHubert(X, k=3)) +plot(pca1, main="ROBPCA-MCD", off=0.03) + +## PCA with the projection algoritm of Hubert +(pca2 <- PcaHubert(X, k=3, mcd=FALSE)) +plot(pca2, main="ROBPCA-SD", off=0.03) + +## PCA with the adjusted for skewness algorithm of Hubert et al (2009) +(pca3 <- PcaHubert(X, k=3, mcd=FALSE, skew=TRUE)) +plot(pca3, main="ROBPCA-AO", off=0.03) diff -Nru r-cran-rrcov-1.6-0/inst/examples/test-ellipse.R r-cran-rrcov-1.6-2/inst/examples/test-ellipse.R --- r-cran-rrcov-1.6-0/inst/examples/test-ellipse.R 2020-01-14 09:11:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/inst/examples/test-ellipse.R 2021-11-17 13:26:58.000000000 +0000 @@ -50,5 +50,5 @@ lines(e2, type="l", col=1) lines(e3, type="l", col=2) lines(e4, type="l", col=2) -lines(e3, type="l", col=3) -lines(e4, type="l", col=3) +lines(e5, type="l", col=3) +lines(e6, type="l", col=3) diff -Nru r-cran-rrcov-1.6-0/inst/NEWS.Rd r-cran-rrcov-1.6-2/inst/NEWS.Rd --- r-cran-rrcov-1.6-0/inst/NEWS.Rd 2021-08-27 20:56:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/inst/NEWS.Rd 2022-02-08 20:28:29.000000000 +0000 @@ -4,16 +4,49 @@ \title{News for \R Package \pkg{rrcov}} \encoding{UTF-8} +\section{CHANGES in rrcov VERSION 1.6-2 (2022-02-08)}{ + \subsection{NEW FEATURES}{ + \itemize{ + \item Examples for PCA/adjustment for skewed data and PCA/percentage of explained + variance added + } + } + \subsection{BUG FIXES}{ + \itemize{ + \item minor differences in tests for PcaProj() on some platforms fixed + \item scoreplot() corrected to show the labels of the samples + } + } +} +\section{CHANGES in rrcov VERSION 1.6-1 (2022-01-21)}{ + \subsection{NEW FEATURES}{ + \itemize{ + \item Data set Fruit added: fruit.rda + \item URLs in Rd files replaced by DOIs to fix for the migration of the + www.jstatsoft.org to a new editorial system (see mail from Achim Zeileis from 06.10.2021) + } + } + \subsection{BUG FIXES}{ + \itemize{ + \item Fixed a problem when showing the percentage of explained variance in + summary() of all PCA functions when k is chosen to be less than the number of variables in the + input data matrix (k < p). The returned object contains now additionally + the rank of the input matrix, the original eigenvalues (of all variables) + and the original total variance, if available. + } + } +} \section{CHANGES in rrcov VERSION 1.6-0 (2021-08-27)}{ \subsection{NEW FEATURES}{ \itemize{ \item PcaHubert: option for adjusted outlyingness for skewed data added \item Data set Computer Hardware added: machines.rda + \item Data set Wolves added: wolves.rda } } \subsection{BUG FIXES}{ \itemize{ - \item Fixed some URLs, particularly the reference to https.javasoft.org + \item Fixed some URLs, particularly the reference to javasoft.org } } } diff -Nru r-cran-rrcov-1.6-0/man/CovClassic-class.Rd r-cran-rrcov-1.6-2/man/CovClassic-class.Rd --- r-cran-rrcov-1.6-0/man/CovClassic-class.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovClassic-class.Rd 2021-11-16 19:10:27.000000000 +0000 @@ -41,10 +41,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } %\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} diff -Nru r-cran-rrcov-1.6-0/man/CovClassic.Rd r-cran-rrcov-1.6-2/man/CovClassic.Rd --- r-cran-rrcov-1.6-0/man/CovClassic.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovClassic.Rd 2021-11-16 19:10:59.000000000 +0000 @@ -23,10 +23,9 @@ An object of class \code{"CovClassic"}. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } %\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} diff -Nru r-cran-rrcov-1.6-0/man/Cov-class.Rd r-cran-rrcov-1.6-2/man/Cov-class.Rd --- r-cran-rrcov-1.6-0/man/Cov-class.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/Cov-class.Rd 2021-11-16 19:10:30.000000000 +0000 @@ -73,14 +73,11 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } -%\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} -%\seealso{} \examples{ showClass("Cov") } diff -Nru r-cran-rrcov-1.6-0/man/CovControl-class.Rd r-cran-rrcov-1.6-2/man/CovControl-class.Rd --- r-cran-rrcov-1.6-0/man/CovControl-class.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovControl-class.Rd 2021-11-16 19:14:20.000000000 +0000 @@ -17,10 +17,9 @@ No methods defined with class "CovControl" in the signature. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } %\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} diff -Nru r-cran-rrcov-1.6-0/man/CovControlMcd-class.Rd r-cran-rrcov-1.6-2/man/CovControlMcd-class.Rd --- r-cran-rrcov-1.6-0/man/CovControlMcd-class.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovControlMcd-class.Rd 2021-11-16 19:16:12.000000000 +0000 @@ -56,10 +56,9 @@ object and will return the obtained \code{CovRobust} object} }} \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } %\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} diff -Nru r-cran-rrcov-1.6-0/man/CovControlMcd.Rd r-cran-rrcov-1.6-2/man/CovControlMcd.Rd --- r-cran-rrcov-1.6-0/man/CovControlMcd.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovControlMcd.Rd 2021-11-16 19:16:38.000000000 +0000 @@ -43,14 +43,11 @@ A \code{CovControlMcd} object } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } -%\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} -%\seealso{} \examples{ ## the following two statements are equivalent ctrl1 <- new("CovControlMcd", alpha=0.75) diff -Nru r-cran-rrcov-1.6-0/man/CovControlMest-class.Rd r-cran-rrcov-1.6-2/man/CovControlMest-class.Rd --- r-cran-rrcov-1.6-0/man/CovControlMest-class.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovControlMest-class.Rd 2021-11-16 19:17:24.000000000 +0000 @@ -42,14 +42,11 @@ } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } -%\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} -%\seealso{} \examples{ ## the following two statements are equivalent ctrl1 <- new("CovControlMest", r=0.4) diff -Nru r-cran-rrcov-1.6-0/man/CovControlMest.Rd r-cran-rrcov-1.6-2/man/CovControlMest.Rd --- r-cran-rrcov-1.6-0/man/CovControlMest.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovControlMest.Rd 2021-11-16 19:17:07.000000000 +0000 @@ -27,10 +27,9 @@ A \code{CovControlMest} object } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } %\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} diff -Nru r-cran-rrcov-1.6-0/man/CovControlMMest-class.Rd r-cran-rrcov-1.6-2/man/CovControlMMest-class.Rd --- r-cran-rrcov-1.6-0/man/CovControlMMest-class.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovControlMMest-class.Rd 2021-11-16 19:15:17.000000000 +0000 @@ -45,10 +45,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } %\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} diff -Nru r-cran-rrcov-1.6-0/man/CovControlMMest.Rd r-cran-rrcov-1.6-2/man/CovControlMMest.Rd --- r-cran-rrcov-1.6-0/man/CovControlMMest.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovControlMMest.Rd 2021-11-16 19:15:40.000000000 +0000 @@ -35,10 +35,9 @@ A \code{CovControlSest} object. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } %\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} diff -Nru r-cran-rrcov-1.6-0/man/CovControlMrcd-class.Rd r-cran-rrcov-1.6-2/man/CovControlMrcd-class.Rd --- r-cran-rrcov-1.6-0/man/CovControlMrcd-class.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovControlMrcd-class.Rd 2021-11-16 19:18:30.000000000 +0000 @@ -47,12 +47,10 @@ object and will return the obtained \code{CovRobust} object} }} \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } -%\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} \seealso{ \code{"\linkS4class{CovControlMcd}"} diff -Nru r-cran-rrcov-1.6-0/man/CovControlMrcd.Rd r-cran-rrcov-1.6-2/man/CovControlMrcd.Rd --- r-cran-rrcov-1.6-0/man/CovControlMrcd.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovControlMrcd.Rd 2021-11-16 19:18:02.000000000 +0000 @@ -38,14 +38,11 @@ A \code{CovControlMrcd} object } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } -%\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} -%\seealso{} \examples{ ## the following two statements are equivalent ctrl1 <- new("CovControlMrcd", alpha=0.75) diff -Nru r-cran-rrcov-1.6-0/man/CovControlMve-class.Rd r-cran-rrcov-1.6-2/man/CovControlMve-class.Rd --- r-cran-rrcov-1.6-0/man/CovControlMve-class.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovControlMve-class.Rd 2021-11-16 19:19:16.000000000 +0000 @@ -42,14 +42,11 @@ object and will return the obtained \code{CovRobust} object} }} \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } -%\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} -%\seealso{} \examples{ ## the following two statements are equivalent ctrl1 <- new("CovControlMve", alpha=0.75) diff -Nru r-cran-rrcov-1.6-0/man/CovControlMve.Rd r-cran-rrcov-1.6-2/man/CovControlMve.Rd --- r-cran-rrcov-1.6-0/man/CovControlMve.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovControlMve.Rd 2021-11-16 19:19:01.000000000 +0000 @@ -25,19 +25,15 @@ \item{seed}{starting value for random generator. Default is \code{seed = NULL}} \item{trace}{whether to print intermediate results. Default is \code{trace = FALSE}} } -%\details{} \value{ A \code{CovControlMve} object } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } -%\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} -%\seealso{} \examples{ ## the following two statements are equivalent ctrl1 <- new("CovControlMve", alpha=0.75) diff -Nru r-cran-rrcov-1.6-0/man/CovControlOgk-class.Rd r-cran-rrcov-1.6-2/man/CovControlOgk-class.Rd --- r-cran-rrcov-1.6-0/man/CovControlOgk-class.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovControlOgk-class.Rd 2021-11-16 19:20:12.000000000 +0000 @@ -47,14 +47,11 @@ object and will return the obtained \code{CovRobust} object} }} \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } -%\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} -%\seealso{} \examples{ ## the following two statements are equivalent ctrl1 <- new("CovControlOgk", beta=0.95) diff -Nru r-cran-rrcov-1.6-0/man/CovControlOgk.Rd r-cran-rrcov-1.6-2/man/CovControlOgk.Rd --- r-cran-rrcov-1.6-0/man/CovControlOgk.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovControlOgk.Rd 2021-11-16 19:19:52.000000000 +0000 @@ -59,12 +59,10 @@ Robust estimates, residuals, and outlier detection with multiresponse data. \emph{Biometrics} \bold{28}, 81--124. - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } -%\seealso{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} \examples{ ## the following two statements are equivalent diff -Nru r-cran-rrcov-1.6-0/man/CovControlSde-class.Rd r-cran-rrcov-1.6-2/man/CovControlSde-class.Rd --- r-cran-rrcov-1.6-0/man/CovControlSde-class.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovControlSde-class.Rd 2021-11-16 19:20:52.000000000 +0000 @@ -42,14 +42,11 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } -%\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} -%\seealso{} \examples{ ## the following two statements are equivalent ctrl1 <- new("CovControlSde", nsamp=2000) diff -Nru r-cran-rrcov-1.6-0/man/CovControlSde.Rd r-cran-rrcov-1.6-2/man/CovControlSde.Rd --- r-cran-rrcov-1.6-0/man/CovControlSde.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovControlSde.Rd 2021-11-16 19:20:35.000000000 +0000 @@ -37,14 +37,11 @@ A \code{CovControlSde} object. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } -%\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} -%\seealso{} \examples{ ## the following two statements are equivalent ctrl1 <- new("CovControlSde", nsamp=2000) diff -Nru r-cran-rrcov-1.6-0/man/CovControlSest-class.Rd r-cran-rrcov-1.6-2/man/CovControlSest-class.Rd --- r-cran-rrcov-1.6-0/man/CovControlSest-class.Rd 2020-08-06 21:29:58.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovControlSest-class.Rd 2021-11-16 19:21:28.000000000 +0000 @@ -53,14 +53,11 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } -%\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} -%\seealso{} \examples{ ## the following two statements are equivalent ctrl1 <- new("CovControlSest", bdp=0.4) diff -Nru r-cran-rrcov-1.6-0/man/CovControlSest.Rd r-cran-rrcov-1.6-2/man/CovControlSest.Rd --- r-cran-rrcov-1.6-0/man/CovControlSest.Rd 2020-08-06 21:30:00.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovControlSest.Rd 2021-11-16 19:21:11.000000000 +0000 @@ -42,14 +42,11 @@ A \code{CovControlSest} object. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } -%\note{} \author{Valentin Todorov \email{valentin.todorov@chello.at}} -%\seealso{} \examples{ ## the following two statements are equivalent ctrl1 <- new("CovControlSest", bdp=0.4) diff -Nru r-cran-rrcov-1.6-0/man/CovMcd-class.Rd r-cran-rrcov-1.6-2/man/CovMcd-class.Rd --- r-cran-rrcov-1.6-0/man/CovMcd-class.Rd 2020-08-06 21:30:03.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovMcd-class.Rd 2021-11-16 19:24:29.000000000 +0000 @@ -57,10 +57,9 @@ No methods defined with class \code{"CovMcd"} in the signature. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/CovMcd.Rd r-cran-rrcov-1.6-2/man/CovMcd.Rd --- r-cran-rrcov-1.6-0/man/CovMcd.Rd 2020-08-06 21:30:05.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovMcd.Rd 2021-11-16 19:24:18.000000000 +0000 @@ -101,17 +101,12 @@ Small Sample Corrections for LTS and MCD, \emph{Metrika}, \bold{55}, 111-123. - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } -%\note{ -% The function \code{\link[robustbase]{covMcd}()} on which \code{CovMcd} is based -% will be deprecated i.e. is going to be made obsolete in future versions. -%} \seealso{ \code{\link[MASS]{cov.rob}} from package \pkg{MASS} } diff -Nru r-cran-rrcov-1.6-0/man/CovMest-class.Rd r-cran-rrcov-1.6-2/man/CovMest-class.Rd --- r-cran-rrcov-1.6-0/man/CovMest-class.Rd 2020-08-06 21:30:08.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovMest-class.Rd 2021-11-16 19:22:58.000000000 +0000 @@ -36,10 +36,9 @@ No methods defined with class "CovMest" in the signature. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{Valentin Todorov \email{valentin.todorov@chello.at}} %\note{} diff -Nru r-cran-rrcov-1.6-0/man/covMest-deprecated.Rd r-cran-rrcov-1.6-2/man/covMest-deprecated.Rd --- r-cran-rrcov-1.6-0/man/covMest-deprecated.Rd 2020-08-06 21:30:10.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/covMest-deprecated.Rd 2021-11-16 19:22:55.000000000 +0000 @@ -94,10 +94,9 @@ D.M.Rocke and D.L.Woodruff (1996) Identification of outliers in multivariate data \emph{Journal of the American Statistical Association}, \bold{91}, 1047--1061. - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. - \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. + \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. + \doi{10.18637/jss.v032.i03}. } \seealso{ \code{\link[robustbase]{covMcd}} diff -Nru r-cran-rrcov-1.6-0/man/CovMest.Rd r-cran-rrcov-1.6-2/man/CovMest.Rd --- r-cran-rrcov-1.6-0/man/CovMest.Rd 2020-08-06 21:30:13.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovMest.Rd 2021-11-16 19:22:23.000000000 +0000 @@ -78,10 +78,9 @@ D.M.Rocke and D.L.Woodruff (1996) Identification of outliers in multivariate data \emph{Journal of the American Statistical Association}, \bold{91}, 1047--1061. - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. - \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. + \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. + \doi{10.18637/jss.v032.i03}. } \seealso{ \code{\link[robustbase]{covMcd}}, \code{\link{Cov-class}}, diff -Nru r-cran-rrcov-1.6-0/man/CovMMest-class.Rd r-cran-rrcov-1.6-2/man/CovMMest-class.Rd --- r-cran-rrcov-1.6-0/man/CovMMest-class.Rd 2020-08-06 21:30:15.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovMMest-class.Rd 2021-11-16 19:23:40.000000000 +0000 @@ -40,10 +40,9 @@ No methods defined with class "CovMMest" in the signature. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/CovMMest.Rd r-cran-rrcov-1.6-2/man/CovMMest.Rd --- r-cran-rrcov-1.6-0/man/CovMMest.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovMMest.Rd 2021-11-16 19:23:43.000000000 +0000 @@ -55,10 +55,9 @@ \emph{Robust Statistics: Theory and Methods}. Wiley, New York. - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. - \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. + \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at}} %\note{} diff -Nru r-cran-rrcov-1.6-0/man/CovMrcd-class.Rd r-cran-rrcov-1.6-2/man/CovMrcd-class.Rd --- r-cran-rrcov-1.6-0/man/CovMrcd-class.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovMrcd-class.Rd 2021-11-16 19:26:03.000000000 +0000 @@ -50,10 +50,9 @@ No methods defined with class \code{"CovMrcd"} in the signature. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/CovMrcd.Rd r-cran-rrcov-1.6-2/man/CovMrcd.Rd --- r-cran-rrcov-1.6-0/man/CovMrcd.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovMrcd.Rd 2022-01-21 15:39:19.000000000 +0000 @@ -71,18 +71,18 @@ virtual class \code{\link{CovRobust-class}}. } \references{ - Kris Boudt, Peter Rousseeuw, Steven Vanduffel and Tim Verdonck (2018) - The Minimum Regularized Covariance Determinant estimator. - submitted, available at \url{https://arxiv.org/abs/1701.07086}. + Kris Boudt, Peter Rousseeuw, Steven Vanduffel and Tim Verdonck (2020) + The Minimum Regularized Covariance Determinant estimator, + \emph{Statistics and Computing}, \bold{30}, pp 113--128 + \doi{10.1007/s11222-019-09869-x}. Mia Hubert, Peter Rousseeuw and Tim Verdonck (2012) A deterministic algorithm for robust location and scatter. \emph{Journal of Computational and Graphical Statistics} \bold{21}(3), 618--637. - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Kris Boudt, Peter Rousseeuw, Steven Vanduffel and Tim Verdonk. Improved by Joachim Schreurs and Iwein Vranckx. diff -Nru r-cran-rrcov-1.6-0/man/CovMve-class.Rd r-cran-rrcov-1.6-2/man/CovMve-class.Rd --- r-cran-rrcov-1.6-0/man/CovMve-class.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovMve-class.Rd 2021-11-16 19:26:31.000000000 +0000 @@ -57,10 +57,9 @@ No methods defined with class "CovMve" in the signature. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/CovMve.Rd r-cran-rrcov-1.6-2/man/CovMve.Rd --- r-cran-rrcov-1.6-0/man/CovMve.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovMve.Rd 2021-11-16 19:26:21.000000000 +0000 @@ -79,11 +79,9 @@ R. A. Maronna, D. Martin and V. Yohai (2006). \emph{Robust Statistics: Theory and Methods}. Wiley, New York. - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. - + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} and Matias Salibian-Barrera \email{matias@stat.ubc.ca} diff -Nru r-cran-rrcov-1.6-0/man/CovOgk-class.Rd r-cran-rrcov-1.6-2/man/CovOgk-class.Rd --- r-cran-rrcov-1.6-0/man/CovOgk-class.Rd 2020-08-06 21:30:19.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovOgk-class.Rd 2021-11-16 19:26:55.000000000 +0000 @@ -42,10 +42,9 @@ No methods defined with class "CovOgk" in the signature. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } diff -Nru r-cran-rrcov-1.6-0/man/CovOgk.Rd r-cran-rrcov-1.6-2/man/CovOgk.Rd --- r-cran-rrcov-1.6-0/man/CovOgk.Rd 2020-08-06 21:29:16.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovOgk.Rd 2021-11-16 19:26:44.000000000 +0000 @@ -69,10 +69,9 @@ Robust estimates, residuals, and outlier detection with multiresponse data. \emph{Biometrics} \bold{28}, 81--124. - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} and diff -Nru r-cran-rrcov-1.6-0/man/CovRobust-class.Rd r-cran-rrcov-1.6-2/man/CovRobust-class.Rd --- r-cran-rrcov-1.6-0/man/CovRobust-class.Rd 2020-08-06 21:29:20.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovRobust-class.Rd 2021-11-16 19:27:32.000000000 +0000 @@ -39,14 +39,11 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{Valentin Todorov \email{valentin.todorov@chello.at}} -%\note{} - \seealso{ \code{\link{Cov-class}}, \code{\link{CovMcd-class}}, \code{\link{CovMest-class}}, \code{\link{CovOgk-class}} } diff -Nru r-cran-rrcov-1.6-0/man/CovRobust.Rd r-cran-rrcov-1.6-2/man/CovRobust.Rd --- r-cran-rrcov-1.6-0/man/CovRobust.Rd 2020-08-06 21:29:23.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovRobust.Rd 2021-11-16 19:27:35.000000000 +0000 @@ -42,10 +42,9 @@ An object derived from a \code{CovRobust} object, depending on the selected estimator. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{Valentin Todorov \email{valentin.todorov@chello.at} } diff -Nru r-cran-rrcov-1.6-0/man/CovSde-class.Rd r-cran-rrcov-1.6-2/man/CovSde-class.Rd --- r-cran-rrcov-1.6-0/man/CovSde-class.Rd 2020-08-06 21:29:25.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovSde-class.Rd 2021-11-16 19:28:07.000000000 +0000 @@ -32,10 +32,9 @@ No methods defined with class "CovSde" in the signature. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/CovSde.Rd r-cran-rrcov-1.6-2/man/CovSde.Rd --- r-cran-rrcov-1.6-0/man/CovSde.Rd 2020-08-06 21:29:28.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovSde.Rd 2021-11-16 19:27:55.000000000 +0000 @@ -62,10 +62,9 @@ R. A. Maronna, D. Martin and V. Yohai (2006). \emph{Robust Statistics: Theory and Methods}. Wiley, New York. - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ diff -Nru r-cran-rrcov-1.6-0/man/CovSest-class.Rd r-cran-rrcov-1.6-2/man/CovSest-class.Rd --- r-cran-rrcov-1.6-0/man/CovSest-class.Rd 2020-08-06 21:29:31.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovSest-class.Rd 2021-11-16 19:28:35.000000000 +0000 @@ -40,10 +40,9 @@ No methods defined with class "CovSest" in the signature. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/CovSest.Rd r-cran-rrcov-1.6-2/man/CovSest.Rd --- r-cran-rrcov-1.6-0/man/CovSest.Rd 2020-08-06 21:29:33.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/CovSest.Rd 2021-11-16 19:28:25.000000000 +0000 @@ -114,10 +114,9 @@ R. A. Maronna, D. Martin and V. Yohai (2006). \emph{Robust Statistics: Theory and Methods}. Wiley, New York. - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at}, Matias Salibian-Barrera \email{matias@stat.ubc.ca} and diff -Nru r-cran-rrcov-1.6-0/man/fruit.Rd r-cran-rrcov-1.6-2/man/fruit.Rd --- r-cran-rrcov-1.6-0/man/fruit.Rd 1970-01-01 00:00:00.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/fruit.Rd 2022-02-06 16:53:28.000000000 +0000 @@ -0,0 +1,45 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/datadoc.R +\docType{data} +\name{fruit} +\alias{fruit} +\title{Fruit data set} +\format{ +A data frame with 1096 rows and 257 variables (one grouping variable -- \code{cultivar} -- and 256 measurement variables). +} +\source{ +Colin Greensill (Faculty of Engineering and Physical Systems, Central Queensland +University, Rockhampton, Australia). +} +\usage{ +data(fruit) +} +\description{ +A data set that contains the spectra of six different cultivars of +the same fruit (cantaloupe - \emph{Cucumis melo} L. Cantaloupensis +group) obtained from Colin Greensill (Faculty of Engineering and Physical Systems, Central Queensland +University, Rockhampton, Australia). The total data set contained 2818 spectra measured in 256 wavelengths. +For illustrative purposes are considered only three cultivars out of it, named D, M and +HA with sizes 490, 106 and 500, respectively. Thus the data set thus contains 1096 observations. +For more details about this data set see the references below. +} +\examples{ + + data(fruit) + table(fruit$cultivar) + +} +\references{ +Hubert, M. and Van Driessen, K., (2004). Fast and robust discriminant analysis. + \emph{Computational Statistics and Data Analysis}, \bold{45}(2):301--320. + \doi{10.1016/S0167-9473(02)00299-2}. + + Vanden Branden, K and Hubert, M, (2005). Robust classification in high dimensions based on the SIMCA Method. + \emph{Chemometrics and Intelligent Laboratory Systems}, \bold{79}(1-2), pp. 10--21. + \doi{10.1016/j.chemolab.2005.03.002}. + + Hubert, M, Rousseeuw, PJ and Verdonck, T, (2012). A Deterministic Algorithm for Robust Location and Scatter. + \emph{Journal of Computational and Graphical Statistics}, \bold{21}(3), pp 618--637. + \doi{10.1080/10618600.2012.672100}. +} +\keyword{datasets} diff -Nru r-cran-rrcov-1.6-0/man/LdaClassic-class.Rd r-cran-rrcov-1.6-2/man/LdaClassic-class.Rd --- r-cran-rrcov-1.6-0/man/LdaClassic-class.Rd 2020-08-06 21:29:41.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/LdaClassic-class.Rd 2021-11-16 19:30:40.000000000 +0000 @@ -29,10 +29,9 @@ No methods defined with class "LdaClassic" in the signature. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/LdaClassic.Rd r-cran-rrcov-1.6-2/man/LdaClassic.Rd --- r-cran-rrcov-1.6-0/man/LdaClassic.Rd 2020-08-06 21:29:44.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/LdaClassic.Rd 2021-11-16 19:30:49.000000000 +0000 @@ -24,10 +24,9 @@ Returns an S4 object of class \code{LdaClassic} } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } diff -Nru r-cran-rrcov-1.6-0/man/Lda-class.Rd r-cran-rrcov-1.6-2/man/Lda-class.Rd --- r-cran-rrcov-1.6-0/man/Lda-class.Rd 2020-08-06 21:29:38.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/Lda-class.Rd 2021-11-16 19:30:26.000000000 +0000 @@ -46,10 +46,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/LdaPP-class.Rd r-cran-rrcov-1.6-2/man/LdaPP-class.Rd --- r-cran-rrcov-1.6-0/man/LdaPP-class.Rd 2020-08-06 21:29:48.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/LdaPP-class.Rd 2021-11-16 19:32:19.000000000 +0000 @@ -52,10 +52,9 @@ Projection-pursuit approach to robust linear discriminant analysis \emph{Journal Multivariate Analysis}, Academic Press, Inc., \bold{101}, 2464--2485. - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} and diff -Nru r-cran-rrcov-1.6-0/man/LdaPP.Rd r-cran-rrcov-1.6-2/man/LdaPP.Rd --- r-cran-rrcov-1.6-0/man/LdaPP.Rd 2016-09-06 10:48:49.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/LdaPP.Rd 2022-02-06 16:47:52.000000000 +0000 @@ -114,6 +114,8 @@ ## plot(CA~MG, data=pottery, col=gcol, pch=gpch) +\dontrun{ + ppc <- LdaPP(x, grp, method="class", optim=TRUE) lda.line(ppc, col=1, lwd=2, lty=1) @@ -143,5 +145,7 @@ fit <- LdaPP(origin~., data = pottery) predict(fit) } + +} \keyword{robust} \keyword{multivariate} diff -Nru r-cran-rrcov-1.6-0/man/LdaRobust-class.Rd r-cran-rrcov-1.6-2/man/LdaRobust-class.Rd --- r-cran-rrcov-1.6-0/man/LdaRobust-class.Rd 2020-08-06 21:29:50.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/LdaRobust-class.Rd 2021-11-16 19:31:08.000000000 +0000 @@ -27,10 +27,9 @@ No methods defined with class "LdaRobust" in the signature. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/Linda-class.Rd r-cran-rrcov-1.6-2/man/Linda-class.Rd --- r-cran-rrcov-1.6-0/man/Linda-class.Rd 2020-08-06 21:29:53.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/Linda-class.Rd 2021-11-16 19:31:18.000000000 +0000 @@ -34,10 +34,9 @@ \section{Methods}{No methods defined with class "Linda" in the signature.} \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/Linda.Rd r-cran-rrcov-1.6-2/man/Linda.Rd --- r-cran-rrcov-1.6-0/man/Linda.Rd 2021-09-03 21:46:09.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/Linda.Rd 2021-11-16 19:31:26.000000000 +0000 @@ -54,10 +54,9 @@ Linear Discriminant Analysis Methods. \emph{REVSTAT Statistical Journal}, \bold{5}, p 63--83. - Todorov V and Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. - \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. + \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } diff -Nru r-cran-rrcov-1.6-0/man/machines.Rd r-cran-rrcov-1.6-2/man/machines.Rd --- r-cran-rrcov-1.6-0/man/machines.Rd 2020-08-02 17:56:16.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/machines.Rd 2022-02-06 16:53:28.000000000 +0000 @@ -66,8 +66,7 @@ of central processing units: A relative performance prediction model, \emph{Communications of the ACM}, \bold{30}, 4, pp 308-317. - Kibler, D., Aha, D.W. and Albert, M. (1989). Instance-based prediction - of real-valued attributes. \emph{Computational Intelligence}, Vo.l 5, - 51-57. + M. Hubert, P. J. Rousseeuw and T. Verdonck (2009), Robust PCA for skewed data and + its outlier map, \emph{Computational Statistics & Data Analysis}, \bold{53}, 2264--2274. } \keyword{datasets} diff -Nru r-cran-rrcov-1.6-0/man/PcaClassic-class.Rd r-cran-rrcov-1.6-2/man/PcaClassic-class.Rd --- r-cran-rrcov-1.6-0/man/PcaClassic-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/PcaClassic-class.Rd 2021-11-16 19:33:50.000000000 +0000 @@ -15,6 +15,7 @@ \item{\code{call}:}{Object of class \code{"language"} } \item{\code{center}:}{Object of class \code{"vector"} the center of the data } \item{\code{scale}:}{Object of class \code{"vector"} the scaling applied to each variable } + \item{\code{rank}:}{Object of class \code{"numeric"} the rank of the data matrix } \item{\code{loadings}:}{Object of class \code{"matrix"} the matrix of variable loadings (i.e., a matrix whose columns contain the eigenvectors) } \item{\code{eigenvalues}:}{Object of class \code{"vector"} the eigenvalues } @@ -33,6 +34,8 @@ as outliers and receive a flag equal to zero. The regular observations receive a flag 1 } \item{\code{n.obs}:}{Object of class \code{"numeric"} the number of observations } + \item{\code{eig0}:}{Object of class \code{"vector"} all eigenvalues } + \item{\code{totvar0}:}{Object of class \code{"numeric"} the total variance explained (\code{=sum(eig0)}) } } } \section{Extends}{ @@ -45,10 +48,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/PcaClassic.Rd r-cran-rrcov-1.6-2/man/PcaClassic.Rd --- r-cran-rrcov-1.6-0/man/PcaClassic.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/PcaClassic.Rd 2021-11-19 17:09:06.000000000 +0000 @@ -48,7 +48,7 @@ \item{signflip}{a logical value indicating wheather to try to solve the sign indeterminancy of the loadings - ad hoc approach setting the maximum element in a singular vector to be positive. Default is - \code{signflip = FALSE}} + \code{signflip = TRUE}} \item{crit.pca.distances}{criterion to use for computing the cutoff values for the orthogonal and score distances. Default is 0.975.} \item{trace}{whether to print intermediate results. Default is \code{trace = FALSE}} @@ -59,10 +59,9 @@ virtual class \code{\link{Pca-class}}. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } diff -Nru r-cran-rrcov-1.6-0/man/Pca-class.Rd r-cran-rrcov-1.6-2/man/Pca-class.Rd --- r-cran-rrcov-1.6-0/man/Pca-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/Pca-class.Rd 2021-11-16 19:31:53.000000000 +0000 @@ -28,6 +28,7 @@ \item{\code{call}:}{Object of class \code{"language"} } \item{\code{center}:}{Object of class \code{"vector"} the center of the data } \item{\code{scale}:}{Object of class \code{"vector"} the scaling applied to each variable of the data } + \item{\code{rank}:}{Object of class \code{"numeric"} the rank of the data matrix } \item{\code{loadings}:}{Object of class \code{"matrix"} the matrix of variable loadings (i.e., a matrix whose columns contain the eigenvectors) } \item{\code{eigenvalues}:}{Object of class \code{"vector"} the eigenvalues } @@ -47,6 +48,8 @@ The regular observations receive a flag 1 } \item{crit.pca.distances}{criterion to use for computing the cutoff values for the orthogonal and score distances. Default is 0.975.} \item{\code{n.obs}:}{Object of class \code{"numeric"} the number of observations } + \item{\code{eig0}:}{Object of class \code{"vector"} all eigenvalues } + \item{\code{totvar0}:}{Object of class \code{"numeric"} the total variance explained (\code{=sum(eig0)}) } } } \section{Methods}{ @@ -86,10 +89,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/PcaCov-class.Rd r-cran-rrcov-1.6-2/man/PcaCov-class.Rd --- r-cran-rrcov-1.6-0/man/PcaCov-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/PcaCov-class.Rd 2021-11-16 19:33:57.000000000 +0000 @@ -19,10 +19,10 @@ \describe{ \item{\code{quan}:}{Object of class \code{"numeric"} The quantile \code{h} used throughout the algorithm } - \item{\code{call}, \code{center}, \code{loadings}, + \item{\code{call}, \code{center}, \code{rank}, \code{loadings}, \code{eigenvalues}, \code{scores}, \code{k}, \code{sd}, \code{od}, \code{cutoff.sd}, \code{cutoff.od}, - \code{flag}, \code{n.obs}:}{ + \code{flag}, \code{n.obs}, \code{eig0}, \code{totvar0}:}{ from the \code{"\linkS4class{Pca}"} class. } } @@ -38,10 +38,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/PcaCov.Rd r-cran-rrcov-1.6-2/man/PcaCov.Rd --- r-cran-rrcov-1.6-0/man/PcaCov.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/PcaCov.Rd 2021-11-19 17:09:56.000000000 +0000 @@ -52,7 +52,7 @@ of \code{x}. The value is passed to the underlying function and the result returned is stored in the scale slot. Default is \code{scale=FALSE}.} \item{signflip}{a logical value indicating wheather to try to solve the sign indeterminancy of the loadings - - ad hoc approach setting the maximum element in a singular vector to be positive. Default is \code{signflip = FALSE}} + ad hoc approach setting the maximum element in a singular vector to be positive. Default is \code{signflip = TRUE}} \item{crit.pca.distances}{criterion to use for computing the cutoff values for the orthogonal and score distances. Default is 0.975.} \item{trace}{whether to print intermediate results. Default is \code{trace = FALSE}} @@ -66,10 +66,9 @@ virtual class \code{\link{PcaRobust-class}}. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } diff -Nru r-cran-rrcov-1.6-0/man/pca.distances.Rd r-cran-rrcov-1.6-2/man/pca.distances.Rd --- r-cran-rrcov-1.6-0/man/pca.distances.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/pca.distances.Rd 2021-11-16 19:31:51.000000000 +0000 @@ -34,10 +34,9 @@ M. Hubert, P. J. Rousseeuw, K. Vanden Branden (2005), ROBPCA: a new approach to robust principal components analysis, \emph{Technometrics}, \bold{47}, 64--79. - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. - \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. + \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. + \doi{10.18637/jss.v032.i03}. } \author{Valentin Todorov \email{valentin.todorov@chello.at}} \examples{ diff -Nru r-cran-rrcov-1.6-0/man/PcaGrid-class.Rd r-cran-rrcov-1.6-2/man/PcaGrid-class.Rd --- r-cran-rrcov-1.6-0/man/PcaGrid-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/PcaGrid-class.Rd 2021-11-16 19:34:02.000000000 +0000 @@ -15,7 +15,7 @@ } \section{Slots}{ \describe{ - \item{\code{call}, \code{center}, \code{scale}, \code{loadings}, + \item{\code{call}, \code{center}, \code{scale}, \code{rank}, \code{loadings}, \code{eigenvalues}, \code{scores}, \code{k}, \code{sd}, \code{od}, \code{cutoff.sd}, \code{cutoff.od}, \code{flag}, \code{n.obs}:}{ @@ -34,10 +34,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/PcaGrid.Rd r-cran-rrcov-1.6-2/man/PcaGrid.Rd --- r-cran-rrcov-1.6-0/man/PcaGrid.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/PcaGrid.Rd 2021-11-16 19:34:04.000000000 +0000 @@ -59,14 +59,12 @@ Algorithms for Projection-Pursuit Robust Principal Component Analysis, \emph{Chemometrics and Intelligent Laboratory Systems}, 87, 225. - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } -%\note{} \examples{ # multivariate data with outliers library(mvtnorm) diff -Nru r-cran-rrcov-1.6-0/man/PcaHubert-class.Rd r-cran-rrcov-1.6-2/man/PcaHubert-class.Rd --- r-cran-rrcov-1.6-0/man/PcaHubert-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/PcaHubert-class.Rd 2021-11-16 19:34:07.000000000 +0000 @@ -22,10 +22,10 @@ \item{\code{quan}:}{The quantile \code{h} used throughout the algorithm } \item{\code{skew}:}{Whether the adjusted outlyingness algorithm for skewed data was used} \item{\code{ao}:}{Object of class \code{"Uvector"} Adjusted outlyingness within the robust PCA subspace } - \item{\code{call}, \code{center}, \code{loadings}, + \item{\code{call}, \code{center}, \code{scale}, \code{rank}, \code{loadings}, \code{eigenvalues}, \code{scores}, \code{k}, \code{sd}, \code{od}, \code{cutoff.sd}, \code{cutoff.od}, - \code{flag}, \code{n.obs}:}{ + \code{flag}, \code{n.obs}, \code{eig0}, \code{totvar0}:}{ from the \code{"\linkS4class{Pca}"} class. } } @@ -41,10 +41,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/PcaHubert.Rd r-cran-rrcov-1.6-2/man/PcaHubert.Rd --- r-cran-rrcov-1.6-0/man/PcaHubert.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/PcaHubert.Rd 2021-11-19 17:11:17.000000000 +0000 @@ -67,7 +67,7 @@ of \code{x}. The value is passed to the underlying function and the result returned is stored in the scale slot. Default is \code{scale=FALSE}.} \item{signflip}{a logical value indicating wheather to try to solve the sign indeterminancy of the loadings - - ad hoc approach setting the maximum element in a singular vector to be positive. Default is \code{signflip = FALSE}} + ad hoc approach setting the maximum element in a singular vector to be positive. Default is \code{signflip = TRUE}} \item{crit.pca.distances}{criterion to use for computing the cutoff values for the orthogonal and score distances. Default is 0.975.} \item{trace}{whether to print intermediate results. Default is \code{trace = FALSE}} @@ -132,10 +132,9 @@ M. Hubert, P. J. Rousseeuw and T. Verdonck (2009), Robust PCA for skewed data and its outlier map, \emph{Computational Statistics & Data Analysis}, \bold{53}, 2264--2274. - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. - \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. + \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } diff -Nru r-cran-rrcov-1.6-0/man/PcaLocantore-class.Rd r-cran-rrcov-1.6-2/man/PcaLocantore-class.Rd --- r-cran-rrcov-1.6-0/man/PcaLocantore-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/PcaLocantore-class.Rd 2021-11-16 19:34:11.000000000 +0000 @@ -22,10 +22,10 @@ \describe{ \item{\code{delta}:}{Accuracy parameter} \item{\code{quan}:}{Object of class \code{"numeric"} The quantile h used throughout the algorithm } - \item{\code{call}, \code{center}, \code{scale}, \code{loadings}, + \item{\code{call}, \code{center}, \code{scale}, \code{rank}, \code{loadings}, \code{eigenvalues}, \code{scores}, \code{k}, \code{sd}, \code{od}, \code{cutoff.sd}, \code{cutoff.od}, - \code{flag}, \code{n.obs}:}{ + \code{flag}, \code{n.obs}, \code{eig0}, \code{totvar0}:}{ from the \code{"\linkS4class{Pca}"} class. } } @@ -41,10 +41,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/PcaLocantore.Rd r-cran-rrcov-1.6-2/man/PcaLocantore.Rd --- r-cran-rrcov-1.6-0/man/PcaLocantore.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/PcaLocantore.Rd 2021-11-21 16:10:22.000000000 +0000 @@ -6,7 +6,7 @@ \description{ The Spherical Principal Components procedure was proposed by Locantore et al., (1999) as a functional data analysis method. -The idea is to perform classical PCA on the data, \ +The idea is to perform classical PCA on the data, projected onto a unit sphere. The estimates of the eigenvectors are consistent and the procedure is extremely fast. The simulations of Maronna (2005) show that this method has very good performance. @@ -54,7 +54,7 @@ \item{signflip}{a logical value indicating wheather to try to solve the sign indeterminancy of the loadings - ad hoc approach setting the maximum element in a singular vector to be positive. Default is - \code{signflip = FALSE}} + \code{signflip = TRUE}} \item{crit.pca.distances}{criterion to use for computing the cutoff values for the orthogonal and score distances. Default is 0.975.} \item{trace}{whether to print intermediate results. Default is \code{trace = FALSE}} @@ -78,18 +78,15 @@ R. Maronna (2005). Principal components and orthogonal regression based on robust scales. Technometrics, 47, 264-273. - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. - + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} The SPC algorithm is implemented on the bases of the available from the web site of the book Maronna et al. (2006) code \url{https://www.wiley.com/legacy/wileychi/robust_statistics/} } -%\note{} \examples{ ## PCA of the Hawkins Bradu Kass's Artificial Data ## using all 4 variables diff -Nru r-cran-rrcov-1.6-0/man/PcaProj-class.Rd r-cran-rrcov-1.6-2/man/PcaProj-class.Rd --- r-cran-rrcov-1.6-0/man/PcaProj-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/PcaProj-class.Rd 2021-11-16 19:37:30.000000000 +0000 @@ -15,7 +15,7 @@ } \section{Slots}{ \describe{ - \item{\code{call}, \code{center}, \code{scale}, \code{loadings}, + \item{\code{call}, \code{center}, \code{scale}, \code{rank}, \code{loadings}, \code{eigenvalues}, \code{scores}, \code{k}, \code{sd}, \code{od}, \code{cutoff.sd}, \code{cutoff.od}, \code{flag}, \code{n.obs}:}{ @@ -34,10 +34,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/PcaProj.Rd r-cran-rrcov-1.6-2/man/PcaProj.Rd --- r-cran-rrcov-1.6-0/man/PcaProj.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/PcaProj.Rd 2021-11-16 19:37:32.000000000 +0000 @@ -59,15 +59,12 @@ C. Croux, A. Ruiz-Gazen (2005). High breakdown estimators for principal components: The projection-pursuit approach revisited, \emph{Journal of Multivariate Analysis}, 95, 206--226. - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. - + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } -%\note{} \examples{ # multivariate data with outliers library(mvtnorm) diff -Nru r-cran-rrcov-1.6-0/man/PcaRobust-class.Rd r-cran-rrcov-1.6-2/man/PcaRobust-class.Rd --- r-cran-rrcov-1.6-0/man/PcaRobust-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/PcaRobust-class.Rd 2021-11-16 19:37:35.000000000 +0000 @@ -36,10 +36,9 @@ No methods defined with class "PcaRobust" in the signature. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/pca.scoreplot.Rd r-cran-rrcov-1.6-2/man/pca.scoreplot.Rd --- r-cran-rrcov-1.6-0/man/pca.scoreplot.Rd 2016-09-06 10:48:49.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/pca.scoreplot.Rd 2022-02-08 21:05:04.000000000 +0000 @@ -7,7 +7,7 @@ Produces a score plot from an object (derived from) \code{\link{Pca-class}}. } \usage{ - pca.scoreplot(obj, i=1, j=2, main, id.n=0, \dots) + pca.scoreplot(obj, i=1, j=2, main, id.n, \dots) } \arguments{ @@ -15,8 +15,10 @@ \item{i}{First score coordinate, defaults to \code{i=1}.} \item{j}{Second score coordinate, defaults to \code{j=2}.} \item{main}{The main title of the plot.} - \item{id.n}{ Number of observations to identify by a label. Defaults to \code{id.n=0}.} - \item{\dots}{optional arguments to be passed to the internal graphical functions.} + \item{id.n}{Number of observations to identify by a label. If missing and the + total number of observations is less or equal to 10, all observations will + be labelled.} + \item{\dots}{Optional arguments to be passed to the internal graphical functions.} } %\details{} %\value{} diff -Nru r-cran-rrcov-1.6-0/man/PredictLda-class.Rd r-cran-rrcov-1.6-2/man/PredictLda-class.Rd --- r-cran-rrcov-1.6-0/man/PredictLda-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/PredictLda-class.Rd 2021-11-16 19:37:38.000000000 +0000 @@ -23,10 +23,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{Valentin Todorov \email{valentin.todorov@chello.at}} %\note{} diff -Nru r-cran-rrcov-1.6-0/man/PredictQda-class.Rd r-cran-rrcov-1.6-2/man/PredictQda-class.Rd --- r-cran-rrcov-1.6-0/man/PredictQda-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/PredictQda-class.Rd 2021-11-16 19:36:42.000000000 +0000 @@ -23,10 +23,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{Valentin Todorov \email{valentin.todorov@chello.at}} %\note{} diff -Nru r-cran-rrcov-1.6-0/man/QdaClassic-class.Rd r-cran-rrcov-1.6-2/man/QdaClassic-class.Rd --- r-cran-rrcov-1.6-0/man/QdaClassic-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/QdaClassic-class.Rd 2021-11-16 19:36:46.000000000 +0000 @@ -34,10 +34,9 @@ No methods defined with class "QdaClassic" in the signature. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/QdaClassic.Rd r-cran-rrcov-1.6-2/man/QdaClassic.Rd --- r-cran-rrcov-1.6-0/man/QdaClassic.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/QdaClassic.Rd 2021-11-16 19:36:48.000000000 +0000 @@ -26,10 +26,9 @@ Returns an S4 object of class \code{QdaClassic} } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } diff -Nru r-cran-rrcov-1.6-0/man/Qda-class.Rd r-cran-rrcov-1.6-2/man/Qda-class.Rd --- r-cran-rrcov-1.6-0/man/Qda-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/Qda-class.Rd 2021-11-16 19:36:44.000000000 +0000 @@ -43,10 +43,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/QdaCov-class.Rd r-cran-rrcov-1.6-2/man/QdaCov-class.Rd --- r-cran-rrcov-1.6-0/man/QdaCov-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/QdaCov-class.Rd 2021-11-16 19:36:51.000000000 +0000 @@ -36,10 +36,9 @@ \section{Methods}{No methods defined with class "QdaCov" in the signature.} \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/QdaCov.Rd r-cran-rrcov-1.6-2/man/QdaCov.Rd --- r-cran-rrcov-1.6-0/man/QdaCov.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/QdaCov.Rd 2021-11-16 19:36:53.000000000 +0000 @@ -28,10 +28,9 @@ Returns an S4 object of class \code{QdaCov} } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } diff -Nru r-cran-rrcov-1.6-0/man/QdaRobust-class.Rd r-cran-rrcov-1.6-2/man/QdaRobust-class.Rd --- r-cran-rrcov-1.6-0/man/QdaRobust-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/QdaRobust-class.Rd 2021-11-16 19:36:55.000000000 +0000 @@ -29,10 +29,9 @@ No methods defined with class "QdaRobust" in the signature. } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{ Valentin Todorov \email{valentin.todorov@chello.at} } \seealso{ diff -Nru r-cran-rrcov-1.6-0/man/SummaryCov-class.Rd r-cran-rrcov-1.6-2/man/SummaryCov-class.Rd --- r-cran-rrcov-1.6-0/man/SummaryCov-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/SummaryCov-class.Rd 2021-11-16 19:36:57.000000000 +0000 @@ -33,10 +33,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{Valentin Todorov \email{valentin.todorov@chello.at}} %\note{} diff -Nru r-cran-rrcov-1.6-0/man/SummaryCovRobust-class.Rd r-cran-rrcov-1.6-2/man/SummaryCovRobust-class.Rd --- r-cran-rrcov-1.6-0/man/SummaryCovRobust-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/SummaryCovRobust-class.Rd 2021-11-16 19:37:00.000000000 +0000 @@ -26,10 +26,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{Valentin Todorov \email{valentin.todorov@chello.at}} %\note{} diff -Nru r-cran-rrcov-1.6-0/man/SummaryLda-class.Rd r-cran-rrcov-1.6-2/man/SummaryLda-class.Rd --- r-cran-rrcov-1.6-0/man/SummaryLda-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/SummaryLda-class.Rd 2021-11-16 19:37:16.000000000 +0000 @@ -22,10 +22,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{Valentin Todorov \email{valentin.todorov@chello.at}} %\note{} diff -Nru r-cran-rrcov-1.6-0/man/SummaryPca-class.Rd r-cran-rrcov-1.6-2/man/SummaryPca-class.Rd --- r-cran-rrcov-1.6-0/man/SummaryPca-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/SummaryPca-class.Rd 2021-11-16 19:37:18.000000000 +0000 @@ -23,10 +23,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{Valentin Todorov \email{valentin.todorov@chello.at}} %\note{} diff -Nru r-cran-rrcov-1.6-0/man/SummaryQda-class.Rd r-cran-rrcov-1.6-2/man/SummaryQda-class.Rd --- r-cran-rrcov-1.6-0/man/SummaryQda-class.Rd 2020-08-06 21:33:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/man/SummaryQda-class.Rd 2021-11-16 19:36:40.000000000 +0000 @@ -22,10 +22,9 @@ } } \references{ - Todorov V & Filzmoser P (2009), - An Object Oriented Framework for Robust Multivariate Analysis. + Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. \emph{Journal of Statistical Software}, \bold{32}(3), 1--47. - URL \url{https://www.jstatsoft.org/article/view/v032i03}. + \doi{10.18637/jss.v032.i03}. } \author{Valentin Todorov \email{valentin.todorov@chello.at}} %\note{} diff -Nru r-cran-rrcov-1.6-0/MD5 r-cran-rrcov-1.6-2/MD5 --- r-cran-rrcov-1.6-0/MD5 2021-09-16 05:10:08.000000000 +0000 +++ r-cran-rrcov-1.6-2/MD5 2022-02-10 12:20:03.000000000 +0000 @@ -1,7 +1,7 @@ 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*tests/tldapp.R diff -Nru r-cran-rrcov-1.6-0/NAMESPACE r-cran-rrcov-1.6-2/NAMESPACE --- r-cran-rrcov-1.6-0/NAMESPACE 2020-07-30 09:40:15.000000000 +0000 +++ r-cran-rrcov-1.6-2/NAMESPACE 2022-01-26 21:23:58.000000000 +0000 @@ -5,10 +5,10 @@ importFrom("methods", "is", "new") importFrom(lattice, xyplot, panel.xyplot, panel.abline, ltext) importFrom(mvtnorm, rmvnorm) -importFrom("grDevices", "dev.interactive", "palette") +importFrom("grDevices", "dev.interactive", "palette", "dev.flush", "dev.hold") importFrom("graphics", "abline", "arrows", "axis", "box", "hist", "legend", "lines", "pairs", "par", "points", "rect", - "strwidth", "text", "title") + "strwidth", "text", "title", "barplot") importFrom("stats", ".getXlevels", "cor", "cov", "cov.wt", "cov2cor", "IQR", "dchisq", "density", "dnorm", "ecdf", "mad", "mahalanobis", "median", "model.matrix", "model.response", "na.fail", diff -Nru r-cran-rrcov-1.6-0/R/AllClasses.R r-cran-rrcov-1.6-2/R/AllClasses.R --- r-cran-rrcov-1.6-0/R/AllClasses.R 2020-07-30 10:36:02.000000000 +0000 +++ r-cran-rrcov-1.6-2/R/AllClasses.R 2021-10-11 19:31:24.000000000 +0000 @@ -295,6 +295,7 @@ setClass("Pca", representation(call = "language", center = "vector", scale = "Uvector", + rank = "numeric", loadings = "matrix", eigenvalues = "vector", scores = "matrix", @@ -306,6 +307,8 @@ crit.pca.distances = "numeric", flag = "Uvector", n.obs = "numeric", + eig0 = "vector", + totvar0 = "numeric", "VIRTUAL")) setClass("SummaryPca", representation(pcaobj = "Pca", diff -Nru r-cran-rrcov-1.6-0/R/datadoc.R r-cran-rrcov-1.6-2/R/datadoc.R --- r-cran-rrcov-1.6-0/R/datadoc.R 2021-09-10 13:29:49.000000000 +0000 +++ r-cran-rrcov-1.6-2/R/datadoc.R 2022-02-06 16:50:41.000000000 +0000 @@ -2,7 +2,8 @@ ## VT::03.08.2019 ## ## -## roxygen2::roxygenise("C:/projects/statproj/R/rrcov", clean=TRUE) +## roxygen2::roxygenise("c:/Users/valen/OneDrive/MyRepo/R/rrcov", load_code=roxygen2:::load_installed, clean=TRUE) +## roxygen2::roxygenise("c:/projects/statproj/R/rrcov", load_code=roxygen2:::load_installed, clean=TRUE) ## #' #' @@ -40,9 +41,9 @@ #' of central processing units: A relative performance prediction model, #' \emph{Communications of the ACM}, \bold{30}, 4, pp 308-317. #' -#' Kibler, D., Aha, D.W. and Albert, M. (1989). Instance-based prediction -#' of real-valued attributes. \emph{Computational Intelligence}, Vo.l 5, -#' 51-57. +#' M. Hubert, P. J. Rousseeuw and T. Verdonck (2009), Robust PCA for skewed data and +#' its outlier map, \emph{Computational Statistics & Data Analysis}, \bold{53}, 2264--2274. +#' #' #' @examples #' @@ -132,3 +133,42 @@ #' #' @keywords datasets NULL + +#' +#' Fruit data set +#' +#' A data set that contains the spectra of six different cultivars of +#' the same fruit (cantaloupe - \emph{Cucumis melo} L. Cantaloupensis +#' group) obtained from Colin Greensill (Faculty of Engineering and Physical Systems, Central Queensland +#' University, Rockhampton, Australia). The total data set contained 2818 spectra measured in 256 wavelengths. +#' For illustrative purposes are considered only three cultivars out of it, named D, M and +#' HA with sizes 490, 106 and 500, respectively. Thus the data set thus contains 1096 observations. +#' For more details about this data set see the references below. +#' @name fruit +#' @docType data +#' @usage data(fruit) +#' @format A data frame with 1096 rows and 257 variables (one grouping variable -- \code{cultivar} -- and 256 measurement variables). +#' @source +#' Colin Greensill (Faculty of Engineering and Physical Systems, Central Queensland +#' University, Rockhampton, Australia). +#' +#' @references +#' Hubert, M. and Van Driessen, K., (2004). Fast and robust discriminant analysis. +#' \emph{Computational Statistics and Data Analysis}, \bold{45}(2):301--320. +#' \doi{10.1016/S0167-9473(02)00299-2}. +#' +#' Vanden Branden, K and Hubert, M, (2005). Robust classification in high dimensions based on the SIMCA Method. +#' \emph{Chemometrics and Intelligent Laboratory Systems}, \bold{79}(1-2), pp. 10--21. +#' \doi{10.1016/j.chemolab.2005.03.002}. +#' +#' Hubert, M, Rousseeuw, PJ and Verdonck, T, (2012). A Deterministic Algorithm for Robust Location and Scatter. +#' \emph{Journal of Computational and Graphical Statistics}, \bold{21}(3), pp 618--637. +#' \doi{10.1080/10618600.2012.672100}. +#' +#' @examples +#' +#' data(fruit) +#' table(fruit$cultivar) +#' +#' @keywords datasets +NULL diff -Nru r-cran-rrcov-1.6-0/R/PcaClassic.R r-cran-rrcov-1.6-2/R/PcaClassic.R --- r-cran-rrcov-1.6-0/R/PcaClassic.R 2016-09-06 10:48:49.000000000 +0000 +++ r-cran-rrcov-1.6-2/R/PcaClassic.R 2021-10-11 19:35:16.000000000 +0000 @@ -60,6 +60,8 @@ stop("All data points collapse!") } + myrank <- Xsvd$rank + if(is.logical(scale) && !scale) # no scaling, the defult Xsvd$scale <- vector('numeric', p) + 1 @@ -117,6 +119,8 @@ center <- as.vector(Xsvd$center) scores <- Xsvd$scores[, 1:k, drop=FALSE] scale <- Xsvd$scale + eig0 <- as.vector(Xsvd$eigenvalues) + totvar0 <- sum(eig0) if(is.list(dimnames(data)) && !is.null(dimnames(data)[[1]])) { @@ -130,13 +134,16 @@ ## fix up call to refer to the generic, but leave arg name as 'formula' cl[[1]] <- as.name("PcaClassic") res <- new("PcaClassic", call=cl, + rank=myrank, loadings=loadings, eigenvalues=eigenvalues, center=center, scale=scale, scores=scores, k=k, - n.obs=n) + n.obs=n, + eig0=eig0, + totvar0=totvar0) ## Compute distances and flags res <- pca.distances(res, data, Xsvd$rank, crit.pca.distances) diff -Nru r-cran-rrcov-1.6-0/R/PcaCov.R r-cran-rrcov-1.6-2/R/PcaCov.R --- r-cran-rrcov-1.6-0/R/PcaCov.R 2016-09-06 10:48:49.000000000 +0000 +++ r-cran-rrcov-1.6-2/R/PcaCov.R 2021-10-11 19:45:04.000000000 +0000 @@ -58,7 +58,8 @@ stop("'PcaCov' can only be used with more units than variables") ## verify and set the input parameters: k and kmax - kmax <- max(min(floor(kmax), rankMM(x)),1) + myrank <- rankMM(x) + kmax <- max(min(floor(kmax), myrank),1) if((k <- floor(k)) < 0) k <- 0 else if(k > kmax) { @@ -85,8 +86,8 @@ covx <- if(!is.null(cov.control)) restimate(cov.control, data) else Cov(data) covmat <- list(cov=getCov(covx), center=getCenter(covx), n.obs=covx@n.obs) - ## VT::05.06.2016 -the call to princomp() replaced by an internal function - ## it will habdle the case scale=TRUE and will return also the proper scores + ## VT::05.06.2016 - the call to princomp() replaced by an internal function + ## it will handle the case scale=TRUE and will return also the proper scores out <- .xpc(x, covmat=covmat, scale=scale, signflip=signflip) ## VT::11.28.2015: Choose the number of components k (if not specified) @@ -125,6 +126,8 @@ loadings <- out$loadings[, 1:k, drop=FALSE] eigenvalues <- (sdev^2)[1:k] scores <- out$scores[, 1:k, drop=FALSE] + eig0 <- sdev^2 + totvar0 <- sum(eig0) ###################################################################### names(eigenvalues) <- NULL @@ -139,13 +142,16 @@ ## fix up call to refer to the generic, but leave arg name as 'formula' cl[[1]] <- as.name("PcaCov") res <- new("PcaCov", call=cl, + rank=myrank, loadings=loadings, eigenvalues=eigenvalues, center=center, scale=scale, scores=scores, k=k, - n.obs=n) + n.obs=n, + eig0=eig0, + totvar0=totvar0) ## Compute distances and flags res <- pca.distances(res, x, p, crit.pca.distances) diff -Nru r-cran-rrcov-1.6-0/R/PcaGrid.R r-cran-rrcov-1.6-2/R/PcaGrid.R --- r-cran-rrcov-1.6-0/R/PcaGrid.R 2016-09-06 10:48:49.000000000 +0000 +++ r-cran-rrcov-1.6-2/R/PcaGrid.R 2021-10-11 19:44:06.000000000 +0000 @@ -56,7 +56,8 @@ ## ## verify and set the input parameters: k and kmax ## - kmax <- max(min(floor(kmax), rankMM(x)),1) + myrank <- rankMM(data) + kmax <- max(min(floor(kmax), myrank),1) if(trace) cat("k=", k, ", kmax=", kmax, ".\n", sep="") @@ -80,7 +81,7 @@ { scale <- if(scale) sd else NULL } - out <- PCAgrid(x, k, scale=scale, trace=-1, ...) + out <- PCAgrid(data, k, scale=scale, trace=-1, ...) scores <- predict(out) center <- out$center @@ -100,6 +101,7 @@ ## fix up call to refer to the generic, but leave arg name as `formula' cl[[1]] <- as.name("PcaGrid") res <- new("PcaGrid", call=cl, + rank=myrank, loadings=loadings, eigenvalues=eigenvalues, center=center, @@ -109,6 +111,6 @@ n.obs=n) ## Compute distances and flags - res <- pca.distances(res, x, p, crit.pca.distances) + res <- pca.distances(res, data, p, crit.pca.distances) return(res) } diff -Nru r-cran-rrcov-1.6-0/R/PcaHubert.R r-cran-rrcov-1.6-2/R/PcaHubert.R --- r-cran-rrcov-1.6-0/R/PcaHubert.R 2021-08-31 22:12:35.000000000 +0000 +++ r-cran-rrcov-1.6-2/R/PcaHubert.R 2021-10-11 19:42:05.000000000 +0000 @@ -111,6 +111,8 @@ if(Xsvd$rank == 0) stop("All data points collapse!") + myrank <- Xsvd$rank + ## VT::27.08.2010: introduce 'scale' parameter; return the scale in the value object ## myscale = if(is.logical(scale) && !scale) vector('numeric', p) + 1 else Xsvd$scale @@ -197,6 +199,16 @@ rank <- ncol(X) ## The covariance matrix is not singular ev <- X.mcd.svd$d + if(trace) + cat("\nEigenvalues of S0: ", ev, "\nTotal variance: ", sum(ev), + "\nExplained variance: ", cumsum(ev)/sum(ev), "\n") + + ## VT::08.10.2021 - fix the explained variance in case when k < p. + ## these will be shown in summary() + eig0 <- ev + totvar0 <- sum(ev) + Hsubsets0 <- c() + ## VT::11.28.2015: Choose the number of components k (if not specified) ## ## Use the test l_k/l_1 >= 10.E-3, i.e. the ratio of @@ -247,12 +259,15 @@ eigenvalues=eigenvalues, center=center, scale=myscale, + rank=myrank, scores=scores, k=k, quan=X.mcd@quan, alpha=alpha, skew=FALSE, ao=NULL, + eig0=eig0, + totvar0=totvar0, n.obs=n) } else # p > n or mcd=FALSE => apply the ROBPCA algorithm @@ -275,11 +290,19 @@ H0 <- order(outl) # index of the observations ordered by (increasing) outlyingness Xh <- X[H0[1:h],,drop=FALSE] # the h data points with smallest outlyingness. - # VT::24.04.2020 Keep Xh as a mtrix, otherwise .classPC will not work. + # VT::24.04.2020 Keep Xh as a matrix (drop=FALSE), otherwise .classPC will not work. Xh.svd <- .classPC(Xh) kmax <- min(Xh.svd$rank, kmax) - if(trace) - cat("\nEigenvalues: ", Xh.svd$eigenvalues, "\n") + if(trace){ + cat("\nEigenvalues of S0: ", Xh.svd$eigenvalues, "\nTotal variance: ", sum(Xh.svd$eigenvalues), + "\nExplained variance: ", cumsum(Xh.svd$eigenvalues)/sum(Xh.svd$eigenvalues), "\n") + } + + ## VT::08.10.2021 - fix the explained variance in case when k < p. + ## these will be shown in summary() + eig0 <- Xh.svd$eigenvalues + totvar0 <- sum(Xh.svd$eigenvalues) + Hsubsets0 <- H0[1:h] ## ## Find the number of PC 'k' @@ -334,7 +357,7 @@ if(trace) { - cat("\n.........: ", cutoffodh) + cat("\nCutoff for the orthogonal distances:\n.........: ", cutoffodh) cat("\numcd.....: ", .crit.od(odh, method="umcd", quan=h), "\n") cat("\nmedmad...: ", .crit.od(odh), "\n") cat("\nskewed...: ", .crit.od(odh, method="skewed"), "\n") @@ -344,7 +367,7 @@ Xh.svd <- .classPC(X[indexset,]) k <- min(Xh.svd$rank, k) if(trace) - cat("\nPerform extra reweighting step (k != rank)", k) + cat("\nPerform extra reweighting step (k != rank)", k, "...Ready.") } ## Project the data points on the subspace spanned by the first k0 eigenvectors @@ -359,7 +382,7 @@ X2 <- as.matrix(X2[ ,1:k]) rot <- as.matrix(rot[ ,1:k]) - ## VT::28.07.2020 - - add adjusted fore skewed data mode + ## VT::28.07.2020 - - add adjusted for skewed data mode ## 3) Adjusted mode for skewed data: Instead of applying the reweighted ## MCD estimator, we calculate the adjusted outlyingness in the ## k-dimensional subspace V_1 and compute the mean and covariance @@ -386,12 +409,15 @@ eigenvalues=eigenvalues, center=center, scale=myscale, + rank=myrank, scores=scores, k=k, quan=h, alpha=alpha, skew=skew, ao=outproj$ao, + eig0=eig0, + totvar0=totvar0, n.obs=n) } @@ -674,6 +700,10 @@ eigenvalues <- ee$values loadings <- rot %*% P6 scores <- (X2 - matrix(rep(X2center, times=n), nrow=n, byrow=TRUE)) %*% P6 + if(trace){ + cat("\nEigenvalues of X2:\n") + print(eigenvalues) + } list(eigenvalues=eigenvalues, loadings=loadings, scores=scores, center=center) } diff -Nru r-cran-rrcov-1.6-0/R/PcaLocantore.R r-cran-rrcov-1.6-2/R/PcaLocantore.R --- r-cran-rrcov-1.6-0/R/PcaLocantore.R 2016-09-06 10:48:49.000000000 +0000 +++ r-cran-rrcov-1.6-2/R/PcaLocantore.R 2021-10-11 19:45:49.000000000 +0000 @@ -60,7 +60,8 @@ ## ## verify and set the input parameters: k and kmax ## - kmax <- max(min(floor(kmax), rankMM(x)),1) + myrank <- rankMM(x) + kmax <- max(min(floor(kmax), myrank),1) if((k <- floor(k)) < 0) k <- 0 else if(k > kmax) { @@ -124,16 +125,22 @@ } ## no scaling - we have already scaled with MAD - out = PcaClassic(y, k=k, kmax=kmax, scale=FALSE, signflip=signflip, ...) + if(k == 0) # let PcaClassic guess the number of components to select + { + out = PcaClassic(y, k=k, kmax=kmax, scale=FALSE, signflip=signflip, ...) + k <- out@k + } + + ## This will return all components, later we will select the first k + out = PcaClassic(y, scale=FALSE, signflip=signflip, ...) - k <- out@k scores = y %*% out@loadings # these are (slightly) diferent from the scores returned by PcaClassic # because PcaClassic will center by the mean the already centered data # use these scores to compute the standard deviations (mad) sdev = apply(scores, 2, "mad") names2 = names(sdev) orsdev = order(sdev) # sort the sdevs (although almost always they will be sorted) - orsdev = rev(orsdev) # use them to sort the laodings, etc. + orsdev = rev(orsdev) # use them to sort the loadings, etc. sdev = sdev[orsdev] scores = scores[,orsdev, drop=FALSE] loadings = out@loadings[,orsdev, drop=FALSE] @@ -147,9 +154,11 @@ scale <- sc center <- doScale(t(as.vector(mu)), center=NULL, scale=1/scale)$x # rescale back to the original data scores <- doScale(x, center, scale)$x %*% loadings # compute the scores - scores <- scores[, 1:k, drop=FALSE] # select only fist k + scores <- scores[, 1:k, drop=FALSE] # select only fist k loadings <- loadings[, 1:k, drop=FALSE] eigenvalues <- (sdev^2)[1:k] + eig0 <- sdev^2 + totvar0 <- sum(eig0) ###################################################################### names(eigenvalues) <- NULL @@ -164,13 +173,16 @@ ## fix up call to refer to the generic, but leave arg name as cl[[1]] <- as.name("PcaLocantore") res <- new("PcaLocantore", call=cl, + rank=myrank, loadings=loadings, eigenvalues=eigenvalues, center=center, scale=scale, scores=scores, k=k, - n.obs=n) + n.obs=n, + eig0=eig0, + totvar0=totvar0) ## Compute distances and flags res <- pca.distances(res, x, p, crit.pca.distances) diff -Nru r-cran-rrcov-1.6-0/R/PcaProj.R r-cran-rrcov-1.6-2/R/PcaProj.R --- r-cran-rrcov-1.6-0/R/PcaProj.R 2020-07-31 22:15:58.000000000 +0000 +++ r-cran-rrcov-1.6-2/R/PcaProj.R 2022-02-07 13:50:05.000000000 +0000 @@ -41,7 +41,8 @@ } PcaProj.default <- function(x, k=0, kmax=ncol(x), - scale=FALSE, na.action = na.fail, crit.pca.distances=0.975, trace=FALSE, ...) + scale=FALSE, na.action = na.fail, crit.pca.distances=0.975, + trace=FALSE, ...) { cl <- match.call() @@ -56,11 +57,13 @@ ## ## verify and set the input parameters: k and kmax ## - kmax <- max(min(floor(kmax), rankMM(x)),1) + myrank <- rankMM(data) + kmax <- max(min(floor(kmax), myrank),1) if((k <- floor(k)) < 0) k <- 0 else if(k > kmax) { - warning(paste("The number of principal components k = ", k, " is larger then kmax = ", kmax, "; k is set to ", kmax,".", sep="")) + warning(paste("The number of principal components k = ", k, + " is larger then kmax = ", kmax, "; k is set to ", kmax,".", sep="")) k <- kmax } if(k != 0) @@ -70,13 +73,11 @@ if(trace) cat("The number of principal components is defined by the algorithm. It is set to ", k,".\n", sep="") } -###################################################################### - if(is.logical(scale)) - { + if(is.logical(scale)) { scale <- if(scale) sd else NULL } - out <- PCAproj(x, k, scale=scale, ...) + out <- PCAproj(data, k, scale=scale, ...) center <- out$center scale <- out$scale @@ -86,8 +87,7 @@ ## VT::31.07.2020 ## scores <- predict(out) ## scores <- as.matrix(scores[, 1:k]) - scores <- (x- matrix(rep(center, nrow(x)), nrow = nrow(x), byrow = TRUE)) %*% loadings - + scores <- (data - matrix(rep(center, nrow(data)), nrow = nrow(data), byrow = TRUE)) %*% loadings eigenvalues <- (sdev^2)[1:k] ###################################################################### @@ -100,6 +100,7 @@ ## fix up call to refer to the generic, but leave arg name as `formula' cl[[1]] <- as.name("PcaProj") res <- new("PcaProj", call=cl, + rank=myrank, loadings=loadings, eigenvalues=eigenvalues, center=center, @@ -109,6 +110,6 @@ n.obs=n) ## Compute distances and flags - res <- pca.distances(res, x, p, crit.pca.distances) + res <- pca.distances(res, data, p, crit.pca.distances) return(res) } diff -Nru r-cran-rrcov-1.6-0/R/Pca.R r-cran-rrcov-1.6-2/R/Pca.R --- r-cran-rrcov-1.6-0/R/Pca.R 2021-08-30 21:33:04.000000000 +0000 +++ r-cran-rrcov-1.6-2/R/Pca.R 2022-02-08 19:00:25.000000000 +0000 @@ -24,12 +24,26 @@ setMethod("summary", "Pca", function(object, ...){ vars <- getEigenvalues(object) vars <- vars/sum(vars) - importance <- rbind("Standard deviation" = getSdev(object), - "Proportion of Variance" = round(vars,5), - "Cumulative Proportion" = round(cumsum(vars), 5)) + + ## If k < p, use the stored initial eigenvalues and total explained variance, if any + if(length(vars) < object@rank) + { + if(length(object@eig0) > 0 && length(object@totvar0) > 0) + { + vars <- object$eig0/object$totvar0 + vars <- vars[1:object$k] + } else + vars <- NULL + } + importance <- if(is.null(vars)) rbind("Standard deviation" = getSdev(object)) + else rbind("Standard deviation" = getSdev(object), + "Proportion of Variance" = round(vars,5), + "Cumulative Proportion" = round(cumsum(vars), 5)) + colnames(importance) <- colnames(getLoadings(object)) new("SummaryPca", pcaobj=object, importance=importance) }) + setMethod("show", "SummaryPca", function(object){ cat("\nCall:\n") @@ -39,6 +53,12 @@ cat("Importance of components:\n") print(object@importance, digits = digits) + + if(nrow(object@importance) == 1) + cat("\nNOTE: Proportion of Variance and Cumulative Proportion are not shown", + "\nbecause the chosen number of components k =", object@pcaobj@k, + "\nis smaller than the rank of the data matrix =", object@pcaobj@rank, "\n") + invisible(object) }) @@ -48,7 +68,7 @@ predict(getPrcomp(object), ...) }) setMethod("screeplot", "Pca", function(x, ...){ - screeplot(getPrcomp(x), ...) + pca.screeplot(x, ...) }) setMethod("biplot", "Pca", function(x, choices=1L:2L, scale=1, ...){ @@ -394,9 +414,32 @@ } } +pca.screeplot <- function (obj, k, type = c("barplot", "lines"), main = deparse1(substitute(obj)), ...) +{ + type <- match.arg(type) + pcs <- if(is.null(obj@eig0) || length(obj@eig0) == 0) obj@eigenvalues else obj@eig0 + k <- if(missing(k)) min(10, length(pcs)) + else min(k, length(pcs)) + + xp <- seq_len(k) + + dev.hold() + on.exit(dev.flush()) + if (type == "barplot") + barplot(pcs[xp], names.arg = names(pcs[xp]), main = main, + ylab = "Variances", ...) + else { + plot(xp, pcs[xp], type = "b", axes = FALSE, main = main, + xlab = "", ylab = "Variances", ...) + axis(2) + axis(1, at = xp, labels = names(pcs[xp])) + } + invisible() +} + ## Score plot of the Pca object 'obj' - scatterplot of ith against jth score ## with superimposed tollerance (0.975) ellipse -pca.scoreplot <- function(obj, i=1, j=2, main, id.n=0, ...) +pca.scoreplot <- function(obj, i=1, j=2, main, id.n, ...) { if(missing(main)) { @@ -404,6 +447,7 @@ } x <- cbind(getScores(obj)[,i], getScores(obj)[,j]) + rownames(x) <- rownames(getScores(obj)) ## VT::11.06.2012 ## Here we assumed that the scores are not correlated and diff -Nru r-cran-rrcov-1.6-0/R/plot-utils.R r-cran-rrcov-1.6-2/R/plot-utils.R --- r-cran-rrcov-1.6-0/R/plot-utils.R 2021-09-13 00:09:45.000000000 +0000 +++ r-cran-rrcov-1.6-2/R/plot-utils.R 2022-02-08 21:04:59.000000000 +0000 @@ -314,7 +314,7 @@ ## The differences to tolEllipsePlot() in robustbase are: ## - customizable (titles, limits, labels, etc) ## - can take either a Cov object or a list (aka cov.wt or covMcd) -## +## - .myellipse <- function (x, xcov, cutoff = NULL, id.n = NULL, @@ -326,8 +326,9 @@ sub="", txt.leg=c("robust", "classical"), col.leg = c("red", "blue"), lty.leg=c("solid", "dashed"), - xlim, - ylim, ...) + xlim, ylim, + off.x, off.y, + ...) { if (is.data.frame(x)) x <- data.matrix(x) @@ -371,8 +372,12 @@ rd <- sqrt(mahalanobis(x, x.loc, x.cov, tol = tol)) if (missing(cutoff) || is.null(cutoff)) cutoff <- sqrt(qchisq(0.975, df = 2)) - if (missing(id.n) || is.null(id.n)) + if (missing(id.n) || is.null(id.n)) { id.n <- sum(rd > cutoff) + if(n <= 10) # if less than 10 observations, show all + id.n <- n + } + ind <- sort(rd, index.return = TRUE)$ix ind <- ind[(n - id.n + 1):n] @@ -381,12 +386,25 @@ if(missing(ylim)) ylim <- y1 - plot(x, xlim = xlim, ylim = ylim, xlab = xlab, ylab = ylab, main = main, sub=sub, ...) + plot(x, xlim = xlim, ylim = ylim, xlab = xlab, ylab = ylab, main = main, + sub=sub, ...) + box() if(id.n > 0) { - xrange <- par("usr") - xrange <- xrange[2] - xrange[1] - text(x[ind, 1] + xrange/50, x[ind, 2], ind) + if(missing(off.x)) + { + xrange <- par("usr") + xrange <- xrange[2] - xrange[1] + off.x <- xrange/50 + } + if(missing(off.y)) + { + xrange <- par("usr") + xrange <- xrange[4] - xrange[3] + off.y <- xrange/50 + } + labels <- if(!is.null(rownames(x))) rownames(x)[ind] else ind + text(x[ind, 1] + off.x, x[ind, 2] + off.y, labels, ...) } points(z2, type = "l", lty = lty.leg[1], col = col.leg[1], ...) diff -Nru r-cran-rrcov-1.6-0/README.md r-cran-rrcov-1.6-2/README.md --- r-cran-rrcov-1.6-0/README.md 2021-07-28 20:13:50.000000000 +0000 +++ r-cran-rrcov-1.6-2/README.md 2022-01-28 10:33:40.000000000 +0000 @@ -1,17 +1,46 @@ -R package providing scalable robust estimators with high breakdown -point. +# `rrcov`: Scalable Robust Estimators with High Breakdown Point + + + +[![CRAN +version](https://www.r-pkg.org/badges/version/rrcov)](https://cran.r-project.org/package=rrcov) +[![R-CMD-check](https://github.com/valentint/rrcov/workflows/R-CMD-check/badge.svg)](https://github.com/valentint/rrcov/actions) +[![downloads](https://cranlogs.r-pkg.org/badges/rrcov)](https://cran.r-project.org/package=rrcov) +[![license](https://img.shields.io/badge/license-GPL--3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0.en.html) + + +The package `rrcov` provides scalable robust estimators with high +breakdown point and covers a large number of robustified multivariate +analysis methods, starting with robust estimators for the multivariate +location and covariance matrix (MCD, MVE, S, MM, SD), the deterministic +versions of MCD, S and MM estimates and regularized versions (MRCD) for +high dimensions. These estimators are used to conduct robust principal +components analysis (`PcaCov()`), linear and quadratic discriminant +analysis (`Linda()`, `Qda()`), MANOVA. Projection pursuit algorithms for +PCA to be applied in high dimensions are also available (`PcaHubert()`, +`PcaGrid()` and `PcaProj()`). ## Installation -You can install ‘rrcov’ from github with: +The `rrcov` package is on CRAN (The Comprehensive R Archive Network) and +the latest release can be easily installed using the command -``` r -# install.packages("remotes") -remotes::install_github("valentint/rrcov") -``` + install.packages("rrcov") + library(rrcov) + +## Building from source + +To install the latest stable development version from GitHub, you can +pull this repository and install it using + + ## install.packages("remotes") + remotes::install_github("valentint/rrcov" --no-build-vignettes) + +Of course, if you have already installed `remotes`, you can skip the +first line (I have commented it out). ## Example @@ -19,10 +48,9 @@ installed: ``` r - library(rrcov) #> Loading required package: robustbase -#> Scalable Robust Estimators with High Breakdown Point (version 1.5-5) +#> Scalable Robust Estimators with High Breakdown Point (version 1.6-1) data(hbk) (out <- CovMcd(hbk)) #> diff -Nru r-cran-rrcov-1.6-0/tests/thubert.R r-cran-rrcov-1.6-2/tests/thubert.R --- r-cran-rrcov-1.6-0/tests/thubert.R 2018-11-14 11:24:40.000000000 +0000 +++ r-cran-rrcov-1.6-2/tests/thubert.R 2022-02-06 16:09:07.000000000 +0000 @@ -1,8 +1,11 @@ -dodata <- function(nrep=1, time=FALSE, short=FALSE, full=TRUE, method=c("hubert", "hubert.mcd", "locantore", "cov", "classic")){ -## Test the function PcaHubert() on the literature datasets: +dodata <- function(nrep=1, time=FALSE, short=FALSE, full=TRUE, + method=c("hubert", "hubert.mcd", "locantore", "cov", "classic", + "grid", "proj")) +{ +## Test the PcaXxx() functions on the literature datasets: ## -## Call PcaHubert() for all regression datasets available in -## robustbase/rrcov and print: +## Call PcaHubert() and the other functions for all regression +## data sets available in robustbase/rrcov and print: ## - execution time (if time == TRUE) ## - loadings ## - eigenvalues @@ -23,6 +26,10 @@ pca <- PcaCov(x) else if(method == "classic") pca <- PcaClassic(x) + else if(method == "grid") + pca <- PcaGrid(x) + else if(method == "proj") + pca <- PcaProj(x) else stop("Undefined PCA method: ", method) @@ -177,7 +184,7 @@ paste(z, padding, sep = "") } -whatis<-function(x){ +whatis <- function(x){ if(is.data.frame(x)) cat("Type: data.frame\n") else if(is.matrix(x)) @@ -266,10 +273,16 @@ dodata(method="hubert.mcd") dodata(method="hubert") -##dodata(method="locantore") -##dodata(method="cov") +dodata(method="locantore") +dodata(method="cov") +dodata(method="grid") + +## IGNORE_RDIFF_BEGIN +dodata(method="proj") +## IGNORE_RDIFF_END -## VT::14.11.2018 - commented out - on some platforms PcaHubert will hoose only 1 PC +## VT::14.11.2018 - commented out - on some platforms PcaHubert will choose only 1 PC ## and will show difference ## test.case.1() + test.case.2() diff -Nru r-cran-rrcov-1.6-0/tests/thubert.Rout.save r-cran-rrcov-1.6-2/tests/thubert.Rout.save --- r-cran-rrcov-1.6-0/tests/thubert.Rout.save 2018-11-14 11:32:46.000000000 +0000 +++ r-cran-rrcov-1.6-2/tests/thubert.Rout.save 2022-02-06 16:21:50.000000000 +0000 @@ -1,7 +1,7 @@ -R Under development (unstable) (2018-11-12 r75592) -- "Unsuffered Consequences" -Copyright (C) 2018 The R Foundation for Statistical Computing -Platform: i386-w64-mingw32/i386 (32-bit) +R Under development (unstable) (2021-10-11 r81035) -- "Unsuffered Consequences" +Copyright (C) 2021 The R Foundation for Statistical Computing +Platform: x86_64-w64-mingw32/x64 (64-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. @@ -15,11 +15,14 @@ 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. -> dodata <- function(nrep=1, time=FALSE, short=FALSE, full=TRUE, method=c("hubert", "hubert.mcd", "locantore", "cov", "classic")){ -+ ## Test the function PcaHubert() on the literature datasets: +> dodata <- function(nrep=1, time=FALSE, short=FALSE, full=TRUE, ++ method=c("hubert", "hubert.mcd", "locantore", "cov", "classic", ++ "grid", "proj")) ++ { ++ ## Test the PcaXxx() functions on the literature datasets: + ## -+ ## Call PcaHubert() for all regression datasets available in -+ ## robustbase/rrcov and print: ++ ## Call PcaHubert() and the other functions for all regression ++ ## data sets available in robustbase/rrcov and print: + ## - execution time (if time == TRUE) + ## - loadings + ## - eigenvalues @@ -40,6 +43,10 @@ + pca <- PcaCov(x) + else if(method == "classic") + pca <- PcaClassic(x) ++ else if(method == "grid") ++ pca <- PcaGrid(x) ++ else if(method == "proj") ++ pca <- PcaProj(x) + else + stop("Undefined PCA method: ", method) + @@ -194,7 +201,7 @@ + paste(z, padding, sep = "") + } > -> whatis<-function(x){ +> whatis <- function(x){ + if(is.data.frame(x)) + cat("Type: data.frame\n") + else if(is.matrix(x)) @@ -278,1435 +285,3432 @@ > ## VT::15.09.2013 - this will render the output independent > ## from the version of the package > suppressPackageStartupMessages(library(rrcov)) -> -> dodata(method="classic") - -Call: dodata(method = "classic") -Data Set n p k e1 e2 -========================================================== -heart 12 2 2 812.379735 9.084962 -Scores: - PC1 PC2 -1 2.7072 1.46576 -2 59.9990 -1.43041 -3 -3.5619 -1.54067 -4 -7.7696 2.52687 -5 14.7660 -0.95822 -6 -20.0489 6.91079 -7 1.4189 2.25961 -8 -34.3308 -4.23717 -9 -6.0487 -0.97859 -10 -33.0102 -3.73143 -11 -18.6372 0.25821 -12 44.5163 -0.54476 -------------- -Call: -PcaClassic(x = x) - -Standard deviations: -[1] 28.5023 3.0141 ----------------------------------------------------------- -starsCYG 47 2 2 0.331279 0.079625 -Scores: - PC1 PC2 -1 0.2072999 0.089973 -2 0.6855999 0.349644 -3 -0.0743007 -0.061028 -4 0.6855999 0.349644 -5 0.1775161 0.015053 -6 0.4223986 0.211351 -7 -0.2926077 -0.516156 -8 0.2188453 0.293607 -9 0.5593696 0.028761 -10 0.0983878 0.074540 -11 0.8258140 -0.711176 -12 0.4167063 0.180244 -13 0.3799883 0.225541 -14 -0.9105236 -0.432014 -15 -0.7418831 -0.125322 -16 -0.4432862 0.048287 -17 -1.0503005 -0.229623 -18 -0.8393302 -0.007831 -19 -0.8126742 -0.195952 -20 0.9842316 -0.688729 -21 -0.6230699 -0.108486 -22 -0.7814875 -0.130933 -23 -0.6017038 0.025840 -24 -0.1857772 0.155474 -25 -0.0020261 0.070412 -26 -0.3640775 0.059510 -27 -0.3458392 -0.069204 -28 -0.1208393 0.053577 -29 -0.6033482 -0.176391 -30 1.1440521 -0.676183 -31 -0.5960920 -0.013765 -32 0.0519296 0.259855 -33 0.1861752 0.167779 -34 1.3802755 -0.632611 -35 -0.6542566 -0.173505 -36 0.5583690 0.392215 -37 0.0561384 0.230152 -38 0.1861752 0.167779 -39 0.1353472 0.241376 -40 0.5355195 0.197080 -41 -0.3980701 0.014294 -42 0.0277576 0.145332 -43 0.2979736 0.234120 -44 0.3049884 0.184614 -45 0.4889809 0.311684 -46 -0.0514512 0.134108 -47 -0.5224950 0.037063 -------------- -Call: -PcaClassic(x = x) - -Standard deviations: -[1] 0.57557 0.28218 ----------------------------------------------------------- -phosphor 18 2 2 220.403422 68.346121 -Scores: - PC1 PC2 -1 4.04290 -15.3459 -2 -22.30489 -1.0004 -3 -24.52683 3.2836 -4 -12.54839 -6.0848 -5 -19.37044 2.2979 -6 15.20366 -19.9424 -7 0.44222 -3.1379 -8 -10.64042 3.6933 -9 -11.67967 5.9670 -10 14.26805 -7.0221 -11 -4.98832 1.5268 -12 8.74986 7.9379 -13 12.26290 6.0251 -14 6.27607 7.5768 -15 17.53246 3.1560 -16 -10.17024 -5.8994 -17 21.05826 5.4492 -18 16.39281 11.5191 -------------- -Call: -PcaClassic(x = x) - -Standard deviations: -[1] 14.8460 8.2672 ----------------------------------------------------------- -stackloss 21 3 3 99.576089 19.581136 -Scores: - PC1 PC2 PC3 -1 20.15352 -4.359452 0.324585 -2 19.81554 -5.300468 0.308294 -3 15.45222 -1.599136 -0.203125 -4 2.40370 -0.145282 2.370302 -5 1.89538 0.070566 0.448061 -6 2.14954 -0.037358 1.409182 -7 4.43153 5.500810 2.468051 -8 4.43153 5.500810 2.468051 -9 -1.47521 1.245404 2.511773 -10 -5.11183 -4.802083 -2.407870 -11 -2.07009 3.667055 -2.261247 -12 -2.66223 2.833964 -3.238659 -13 -4.43589 -2.920053 -2.375287 -14 -0.46404 7.323193 -1.234961 -15 -9.31959 6.232579 -0.056064 -16 -10.33350 3.409533 -0.104938 -17 -14.81094 -9.872607 0.628103 -18 -12.44514 -3.285499 0.742143 -19 -11.85300 -2.452408 1.719555 -20 -5.73994 -2.494520 0.098250 -21 9.98843 1.484952 -3.614198 -------------- -Call: -PcaClassic(x = x) - -Standard deviations: -[1] 9.9788 4.4251 1.8986 ----------------------------------------------------------- -salinity 28 3 3 11.410736 7.075409 -Scores: - PC1 PC2 PC3 -1 -0.937789 -2.40535 0.812909 -2 -1.752631 -2.57774 2.004437 -3 -6.509364 -0.78762 -1.821906 -4 -5.619847 -2.41333 -1.586891 -5 -7.268242 1.61012 1.563568 -6 -4.316558 -3.20411 0.029376 -7 -2.379545 -3.32371 0.703101 -8 0.013514 -3.50586 1.260502 -9 0.265262 -0.16736 -2.886883 -10 1.890755 2.43623 -0.986832 -11 0.804196 2.56656 0.387577 -12 0.935082 -1.03559 -0.074081 -13 1.814839 -1.61087 0.612290 -14 3.407535 -0.15880 2.026088 -15 1.731273 2.95159 -1.840286 -16 -6.129708 7.21368 2.632273 -17 -0.645124 1.06260 0.028697 -18 -1.307532 -2.54679 -0.280273 -19 0.483455 -0.55896 -3.097281 -20 2.053267 0.47308 -1.858703 -21 3.277664 -1.31002 0.453753 -22 4.631644 -0.78005 1.519894 -23 1.864403 5.32790 -0.849694 -24 0.623899 4.29317 0.056461 -25 1.301696 0.37871 -0.646220 -26 2.852126 -0.79527 -0.347711 -27 4.134051 -0.92756 0.449222 -28 4.781679 -0.20467 1.736616 -------------- -Call: -PcaClassic(x = x) - -Standard deviations: -[1] 3.3780 2.6600 1.4836 ----------------------------------------------------------- -hbk 75 3 3 216.162129 1.981077 -Scores: - PC1 PC2 PC3 -1 26.2072 -0.660756 0.503340 -2 27.0406 -0.108506 -0.225059 -3 28.8351 -1.683721 0.263078 -4 29.9221 -0.812174 -0.674480 -5 29.3181 -0.909915 -0.121600 -6 27.5360 -0.599697 0.916574 -7 27.6617 -0.073753 0.676620 -8 26.5576 -0.882312 0.159620 -9 28.8726 -1.074223 -0.673462 -10 27.6643 -1.463829 -0.868593 -11 34.2019 -0.664473 -0.567265 -12 35.4805 -2.730949 -0.259320 -13 34.7544 1.325449 0.749884 -14 38.9522 8.171389 0.034382 -15 -5.5375 0.390704 1.679172 -16 -7.4319 0.803850 1.925633 -17 -8.5880 0.957577 -1.010312 -18 -6.6022 -0.425109 0.625148 -19 -6.5596 1.154721 -0.640680 -20 -5.2525 0.812527 1.377832 -21 -6.2771 0.067747 0.958907 -22 -6.2501 1.325491 -1.104428 -23 -7.2419 0.839808 0.728712 -24 -7.6489 1.131606 0.154897 -25 -9.0763 -0.670721 -0.167577 -26 -5.5967 0.999411 -0.810000 -27 -5.1460 -0.339018 1.326712 -28 -7.1659 -0.993461 0.125933 -29 -8.2104 -0.169338 -0.073569 -30 -6.2499 -1.689222 -0.877481 -31 -7.3180 -0.225795 1.687204 -32 -7.9446 1.473868 -0.541790 -33 -6.3604 1.237472 0.061800 -34 -8.9812 -0.710662 -0.830422 -35 -5.1698 -0.435484 1.102817 -36 -5.9995 -0.058135 -0.713550 -37 -5.8753 0.852882 -1.610556 -38 -8.4501 0.334363 0.404813 -39 -8.1751 -1.300317 0.633282 -40 -7.4495 0.672712 -0.829815 -41 -5.6213 -1.106765 1.395315 -42 -6.8571 -0.900977 -1.509937 -43 -7.0633 1.987372 -1.079934 -44 -6.3763 -1.867647 -0.251224 -45 -8.6456 -0.866053 0.630132 -46 -6.5356 -1.763526 -0.189838 -47 -8.2224 -1.183284 1.615150 -48 -5.6136 -1.100704 1.079239 -49 -5.9907 0.220336 1.443387 -50 -5.2675 0.142923 0.194023 -51 -7.9324 0.324710 1.113289 -52 -7.5544 -1.033884 1.792496 -53 -6.7119 -1.712257 -1.711778 -54 -7.4679 1.856542 0.046658 -55 -7.4666 1.161504 -0.725948 -56 -6.7110 1.574868 0.534288 -57 -8.2571 -0.399824 0.521995 -58 -5.9781 1.312567 0.926790 -59 -5.6960 -0.394338 -0.332938 -60 -6.1017 -0.797579 -1.679359 -61 -5.2628 0.919128 -1.436156 -62 -9.1245 -0.516135 -0.229065 -63 -7.7140 1.659145 0.068510 -64 -4.9886 0.173613 0.865810 -65 -6.6157 -1.479786 0.098390 -66 -7.9511 0.772770 -0.998321 -67 -7.1856 0.459602 0.216588 -68 -8.7345 -0.860784 -1.238576 -69 -8.5833 -0.313481 0.832074 -70 -5.8642 -0.142883 -0.870064 -71 -5.8879 0.186456 0.464467 -72 -7.1865 0.497156 -0.826767 -73 -6.8671 -0.058606 -1.335842 -74 -7.1398 0.727642 -1.422331 -75 -7.2696 -1.347832 -1.496927 -------------- -Call: -PcaClassic(x = x) - -Standard deviations: -[1] 14.70245 1.40751 0.95725 ----------------------------------------------------------- -milk 86 8 8 15.940298 2.771345 -Scores: - PC1 PC2 PC3 PC4 PC5 PC6 PC7 -1 6.471620 1.031110 0.469432 0.5736412 1.0294362 -0.6054039 -0.2005117 -2 7.439545 0.320597 0.081922 -0.6305898 0.7128977 -1.1601053 -0.1170582 -3 1.240654 -1.840458 0.520870 -0.1717469 0.2752079 -0.3815506 0.6004089 -4 5.952685 -1.856375 1.638710 0.3358626 -0.5834205 -0.0665348 -0.1580799 -5 -0.706973 0.261795 0.423736 0.2916399 -0.5307716 -0.3325563 -0.0062349 -6 2.524050 0.293380 -0.572997 0.2466367 -0.3497882 0.0386014 -0.1418131 -7 3.136085 -0.050202 -0.818165 -0.0451560 -0.5226337 -0.1597194 0.1669050 -8 3.260390 0.312365 -0.110776 0.4908006 -0.5225353 -0.1972222 -0.1068433 -9 -0.808914 -2.355785 1.344204 -0.4743284 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-1.2686e-03 -16 -1.8441e-03 -17 -2.1068e-03 -18 -5.7816e-04 -19 -1.2330e-03 -20 3.3857e-05 -21 3.8623e-04 -22 1.3035e-04 -23 -3.8648e-04 -24 -1.7400e-04 -25 -3.9196e-04 -26 -7.6996e-04 -27 -4.8042e-04 -28 -2.0628e-04 -29 -4.5672e-04 -30 -1.4716e-04 -31 -4.6385e-05 -32 -2.0481e-04 -33 -3.0020e-04 -34 -5.8179e-05 -35 1.3870e-04 -36 -6.7177e-04 -37 -3.0799e-04 -38 6.2140e-04 -39 4.5912e-04 -40 -3.7165e-04 -41 -5.4362e-04 -42 -1.0155e-03 -43 1.3449e-04 -44 -5.4761e-04 -45 1.0300e-03 -46 1.1039e-03 -47 -6.4858e-04 -48 -7.6886e-05 -49 3.2590e-04 -50 8.6845e-05 -51 4.9423e-04 -52 9.2973e-04 -53 4.4342e-04 -54 4.9888e-04 -55 7.2171e-04 -56 -3.2133e-05 -57 -1.8101e-04 -58 -5.4969e-06 -59 -8.3841e-04 -60 5.9446e-05 -61 -6.5683e-05 -62 -3.4073e-04 -63 -6.5145e-04 -64 -6.5145e-04 -65 1.4986e-04 -66 2.8096e-04 -67 -6.5170e-05 -68 -1.3775e-04 -69 6.8225e-06 -70 -1.6290e-04 -71 3.9009e-04 -72 -1.3981e-04 -73 6.2613e-04 -74 2.6513e-03 -75 3.7088e-04 -76 9.9539e-04 -77 1.2979e-03 -78 5.6500e-04 -79 3.0940e-04 -80 8.7993e-04 -81 -3.1353e-04 -82 4.9625e-04 -83 -6.3951e-04 -84 -4.5582e-04 -85 5.9440e-04 -86 -3.6234e-04 -------------- -Call: -PcaClassic(x = x) - -Standard deviations: -[1] 3.99253025 1.66473582 1.10660264 0.96987790 0.33004256 0.29263512 0.20843280 -[8] 0.00074024 ----------------------------------------------------------- -bushfire 38 5 5 38435.075910 1035.305774 -Scores: - PC1 PC2 PC3 PC4 PC5 -1 -111.9345 4.9970 -1.00881 -1.224361 3.180569 -2 -113.4128 7.4784 -0.79170 -0.235184 2.385812 -3 -105.8364 10.9615 -3.15662 -0.251662 1.017328 -4 -89.1684 8.7232 -6.15080 -0.075611 1.431111 -5 -58.7216 -1.9543 -12.70661 -0.151328 1.425570 -6 -35.0370 -12.8434 -17.06841 -0.525664 3.499743 -7 -250.2123 -49.4348 23.31261 -19.070238 0.647348 -8 -292.6877 -69.7708 -21.30815 13.093808 -1.288764 -9 -294.0765 -70.9903 -23.96326 14.940985 -0.939076 -10 -290.0193 -57.3747 3.51346 1.858995 0.083107 -11 -289.8168 -43.3207 16.08046 -1.745099 -1.506042 -12 -290.8645 6.2503 40.52173 -7.496479 -0.033767 -13 -232.6865 41.8090 37.19429 -1.280348 -0.470837 -14 9.8483 25.1954 -14.56970 0.538484 1.772046 -15 137.1924 11.8521 -37.12452 -5.130459 -0.586695 -16 92.9804 10.3923 -24.97267 -7.551314 -1.867125 -17 90.4493 10.5630 -21.92735 -5.669651 -1.001362 -18 78.6325 5.2211 -19.74718 -6.107880 -1.939986 -19 82.1178 3.6913 -21.37810 -4.259855 -1.278838 -20 92.9044 7.1961 -21.22900 -4.125571 -0.127089 -21 74.9157 10.2991 -16.60924 -5.660751 -0.406343 -22 66.7350 12.0460 -16.73298 -4.669080 1.333436 -23 -62.1981 22.7394 6.03613 -5.182356 -0.453624 -24 -116.5696 32.3182 12.74846 -1.465657 -0.097851 -25 -53.8907 22.4278 -2.18861 -2.742014 -0.990071 -26 -60.6384 20.2952 -3.05206 -2.953685 -0.629061 -27 -74.7621 28.9067 -0.65817 1.473357 -0.443957 -28 -50.2202 37.3457 -1.44989 5.530426 -1.073521 -29 -38.7483 50.2749 2.34469 10.156457 -0.416262 -30 -93.3887 51.7884 20.08872 8.798781 -1.620216 -31 35.3096 41.7158 13.46272 14.464358 -0.475973 -32 290.8493 3.5924 7.41501 15.244293 2.141354 -33 326.7236 -29.8194 15.64898 2.612061 0.064931 -34 322.9095 -30.6372 16.21520 1.248005 -0.711322 -35 328.5307 -29.9533 16.49656 1.138916 0.974792 -36 325.6791 -30.6990 16.83840 -0.050949 -1.211360 -37 323.8136 -30.7474 19.55764 -1.545150 -0.267580 -38 325.2991 -30.5350 20.31878 -1.928580 -0.120425 -------------- -Call: -PcaClassic(x = x) - -Standard deviations: -[1] 196.0487 32.1762 18.4819 6.9412 1.3510 ----------------------------------------------------------- -========================================================== -> dodata(method="hubert.mcd") - -Call: dodata(method = "hubert.mcd") -Data Set n p k e1 e2 -========================================================== -heart 12 2 2 602.892739 7.727093 -Scores: - PC1 PC2 -1 -12.2285 0.86283 -2 -68.9906 -7.43256 -3 -5.7035 -1.53793 -4 -1.8988 2.90891 -5 -24.0044 -2.68946 -6 9.9115 8.43321 -7 -11.0210 1.77484 -8 25.1826 -1.31573 -9 -3.2809 -0.74345 -10 23.8200 -0.93701 -11 9.1344 1.67701 -12 -53.6607 -5.08826 -------------- -Call: -PcaHubert(x = x, k = p) - -Standard deviations: -[1] 24.5539 2.7798 ----------------------------------------------------------- -starsCYG 47 2 2 0.381108 0.008040 -Scores: - PC1 PC2 -1 -0.285731 -0.0899858 -2 -0.819689 0.0153191 -3 0.028077 -0.1501882 -4 -0.819689 0.0153191 -5 -0.234971 -0.1526225 -6 -0.527231 -0.0382380 -7 0.372118 -0.5195605 -8 -0.357448 0.1009508 -9 -0.603553 -0.2533541 -10 -0.177170 -0.0722541 -11 -0.637339 -1.0390758 -12 -0.512526 -0.0662337 -13 -0.490978 -0.0120517 -14 0.936868 -0.2550656 -15 0.684479 -0.0125787 -16 0.347708 0.0641382 -17 1.009966 -0.0202111 -18 0.742477 0.1286170 -19 0.773105 -0.0588983 -20 -0.795247 -1.0648673 -21 0.566048 -0.0319223 -22 0.723956 -0.0061308 -23 0.505616 0.0899297 -24 0.069956 0.0896997 -25 -0.080090 -0.0462652 -26 0.268755 0.0512425 -27 0.289710 -0.0770574 -28 0.038341 -0.0269216 -29 0.567463 -0.1026188 -30 -0.951542 -1.1005280 -31 0.512064 0.0504528 -32 -0.188059 0.1184850 -33 -0.288758 -0.0094200 -34 -1.190016 -1.1293460 -35 0.615197 -0.0846898 -36 -0.710930 0.0938781 -37 -0.183223 0.0888774 -38 -0.288758 -0.0094200 -39 -0.262177 0.0759816 -40 -0.630957 -0.0855773 -41 0.314679 0.0182135 -42 -0.130850 0.0163715 -43 -0.415248 0.0205825 -44 -0.407188 -0.0287636 -45 -0.620693 0.0376892 -46 -0.051896 0.0292672 -47 0.426662 0.0770340 -------------- -Call: -PcaHubert(x = x, k = p) - -Standard deviations: -[1] 0.617339 0.089666 ----------------------------------------------------------- -phosphor 18 2 2 356.981009 40.133815 -Scores: - PC1 PC2 -1 -2.89681 -18.08811 -2 21.34021 -0.40854 -3 22.98065 4.13006 -4 12.33544 -6.72947 -5 17.99823 2.47611 -6 -13.35773 -24.10967 -7 -0.92957 -5.51314 -8 9.16061 2.71354 -9 9.89243 5.10403 -10 -14.12600 -11.17832 -11 3.84175 -0.17605 -12 -10.61905 4.37646 -13 -13.85065 2.01919 -14 -8.11927 4.34325 -15 -18.69805 -1.51673 -16 9.95352 -6.85784 -17 -22.49433 0.29387 -18 -18.66592 6.92359 -------------- -Call: -PcaHubert(x = x, k = p) - -Standard deviations: -[1] 18.8939 6.3351 ----------------------------------------------------------- -stackloss 21 3 3 90.759236 22.197591 -Scores: - PC1 PC2 PC3 -1 -20.323997 10.26124 0.92041 -2 -19.761418 11.08797 0.92383 -3 -16.469919 6.43190 0.22593 -4 -4.171902 1.68262 2.50695 -5 -3.756174 1.40774 0.57004 -6 -3.964038 1.54518 1.53850 -7 -7.547376 -3.27780 2.48643 -8 -7.547376 -3.27780 2.48643 -9 -0.763294 -0.63699 2.53518 -10 4.214079 4.46296 -2.28315 -11 -0.849132 -2.97767 -2.31393 -12 -0.078689 -2.28838 -3.27896 -13 3.088921 2.80948 -2.28999 -14 -3.307313 -6.14718 -1.35916 -15 5.552354 -7.34201 -0.32057 -16 7.240091 -4.86180 -0.31031 -17 14.908334 6.84995 0.70603 -18 10.970281 1.06279 0.68209 -19 10.199838 0.37350 1.64712 -20 4.273564 1.99328 0.14526 -21 -11.992249 2.19025 -3.37391 -------------- -Call: -PcaHubert(x = x, k = p) - -Standard deviations: -[1] 9.5268 4.7114 2.3614 ----------------------------------------------------------- -salinity 28 3 3 14.598180 5.145994 -Scores: - PC1 PC2 PC3 -1 1.68712 1.62591 0.19812128 -2 2.35772 2.37290 1.24965734 -3 6.80132 -2.14412 0.68142276 -4 6.41982 -0.61348 -0.31907921 -5 6.36697 -1.98030 4.87319903 -6 5.22050 1.20864 0.10252555 -7 3.34007 2.02950 0.00064329 -8 1.06220 2.89801 -0.35658064 -9 0.34692 -2.20572 -1.71677710 -10 -2.21421 -2.74842 0.76862599 -11 -1.40111 -2.16163 2.21124383 -12 -0.38242 0.32284 -0.23732191 -13 -1.12809 1.33152 -0.28800043 -14 -3.24998 1.35943 1.17514969 -15 -2.11006 -3.70114 0.45102357 -16 3.46920 -5.41242 8.56937909 -17 0.46682 -1.46753 1.48992481 -18 2.21807 0.99168 -0.61894625 -19 0.28525 -2.00333 -2.16450483 -20 -1.66639 -1.76768 -1.06946404 -21 -2.58106 1.23534 -0.65557612 -22 -4.15573 1.71244 0.08170141 -23 -3.07670 -4.87628 2.53200755 -24 -1.70808 -3.71657 2.99305849 -25 -1.08172 -1.05713 0.02468813 -26 -2.23187 0.27323 -0.85760867 -27 -3.50498 1.07657 -0.68503455 -28 -4.49819 1.43219 0.53416609 -------------- -Call: -PcaHubert(x = x, k = p) - -Standard deviations: -[1] 3.8208 2.2685 1.2048 ----------------------------------------------------------- -hbk 75 3 3 1.966655 1.617943 -Scores: - PC1 PC2 PC3 -1 -31.105415 4.714217 10.4566165 -2 -31.707650 5.748724 10.7682402 -3 -33.366131 4.625897 12.1570167 -4 -34.173377 6.069657 12.4466895 -5 -33.780418 5.508823 11.9872893 -6 -32.493478 4.684595 10.5679819 -7 -32.592637 5.235522 10.3765493 -8 -31.293363 4.865797 10.9379676 -9 -33.160964 5.714260 12.3098920 -10 -31.919786 5.384537 12.3374332 -11 -38.231962 6.810641 13.5994385 -12 -39.290479 5.393906 15.2942554 -13 -39.418445 7.326461 11.5194898 -14 -43.906584 13.214819 8.3282743 -15 -1.906326 -0.716061 -0.8635112 -16 -0.263255 -0.926016 -1.9009292 -17 1.776489 1.072332 -0.5496140 -18 -0.464648 -0.702441 0.0482897 -19 -0.267826 1.283779 -0.2925812 -20 -2.122108 -0.165970 -0.8924686 -21 -0.937217 -0.548532 -0.4132196 -22 -0.423273 1.781869 -0.0323061 -23 -0.047532 -0.018909 -1.1259327 -24 0.490041 0.520202 -1.1065753 -25 2.143049 -0.720869 -0.0495474 -26 -1.094748 1.459175 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0.710345 -1.3708230 -57 1.115629 -0.888816 -0.4186014 -58 -1.351288 0.374815 -1.1980618 -59 -0.998016 0.151228 0.9007970 -60 -0.124017 0.764846 1.9005963 -61 -1.189858 1.905264 0.7721322 -62 2.190589 -0.579614 -0.1377914 -63 0.518278 0.931130 -1.4534768 -64 -2.124566 -0.194391 -0.0327092 -65 -0.154218 -1.050861 1.1309885 -66 1.197852 1.044147 -0.2265269 -67 0.114174 0.094763 -0.5168926 -68 2.201115 -0.032271 0.8573493 -69 1.307843 -1.104815 -0.7741270 -70 -0.691449 0.676665 1.0004603 -71 -1.150975 -0.050861 -0.0717068 -72 0.457293 0.861871 0.1026350 -73 0.392258 0.897451 0.9178065 -74 0.584658 1.450471 0.3201857 -75 0.972517 0.063777 1.8223995 -------------- -Call: -PcaHubert(x = x, k = p) - -Standard deviations: -[1] 1.4024 1.2720 1.1801 ----------------------------------------------------------- -milk 86 8 8 6.897629 2.890481 -Scores: - PC1 PC2 PC3 PC4 PC5 PC6 PC7 -1 -5.710924 -1.346213 0.01332091 -0.3709242 -0.566813 0.7529298 -1.2525433 -2 -6.578612 -0.440749 1.16354746 0.2870685 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-0.0150514 -82 -2.709588 1.464049 -0.12598126 -0.3828567 0.213647 -0.1425385 0.1552827 -83 -2.213670 0.059563 0.87565603 0.1255703 -0.082005 0.2189829 -0.2938264 -84 -0.242242 -0.483552 2.05089334 -0.0681005 -0.101578 0.1304632 -0.2218093 -85 -1.032129 2.375018 -2.19321259 0.2332079 -0.066379 0.1854598 -0.0873859 -86 0.015327 -0.948155 1.39530555 0.2701225 -0.268889 0.0578145 0.1608678 - PC8 -1 2.1835e-03 -2 1.6801e-03 -3 1.6623e-03 -4 2.6286e-04 -5 9.5884e-04 -6 1.4430e-03 -7 1.8784e-04 -8 6.8473e-04 -9 -6.8490e-04 -10 1.1565e-04 -11 5.6907e-06 -12 -1.8395e-03 -13 -2.1582e-03 -14 -1.6294e-03 -15 -1.6964e-03 -16 -1.9664e-03 -17 -2.2448e-03 -18 -6.5884e-04 -19 -1.1536e-03 -20 2.6887e-04 -21 3.3199e-05 -22 1.1170e-04 -23 -1.7617e-04 -24 -2.1577e-04 -25 -6.1495e-04 -26 -7.2903e-04 -27 -6.8773e-04 -28 -2.0742e-04 -29 -2.6937e-04 -30 -6.7472e-05 -31 -1.3222e-04 -32 -1.6516e-04 -33 -1.8836e-04 -34 -1.1273e-04 -35 3.0703e-05 -36 -3.0311e-04 -37 -1.9380e-04 -38 5.5526e-04 -39 4.1987e-04 -40 8.4807e-05 -41 8.8725e-04 -42 -6.5647e-04 -43 4.3202e-04 -44 -5.3330e-04 -45 8.9161e-04 -46 1.1588e-03 -47 -1.2714e-03 -48 -4.0376e-04 -49 4.1280e-06 -50 3.0116e-04 -51 5.8510e-05 -52 3.3236e-04 -53 4.0982e-04 -54 4.0428e-04 -55 6.1600e-04 -56 -4.0496e-05 -57 -1.8342e-04 -58 -1.6748e-04 -59 -1.0894e-03 -60 -2.6876e-04 -61 -5.8951e-05 -62 -1.5517e-04 -63 -7.9933e-04 -64 -7.9933e-04 -65 2.2592e-05 -66 2.4984e-05 -67 -2.2714e-04 -68 -3.3991e-04 -69 -3.0375e-04 -70 3.4033e-03 -71 2.3288e-05 -72 -3.4126e-04 -73 2.5528e-04 -74 2.2760e-03 -75 -2.8985e-04 -76 7.9077e-04 -77 9.4636e-04 -78 4.9099e-04 -79 3.0501e-04 -80 6.5280e-04 -81 -3.6570e-04 -82 4.9966e-04 -83 -4.3245e-04 -84 -4.6152e-04 -85 7.4691e-04 -86 -6.1103e-04 -------------- -Call: -PcaHubert(x = x, k = p) - -Standard deviations: -[1] 2.62633379 1.70014141 1.01464625 0.36921951 0.21696728 0.19573429 0.17585482 -[8] 0.00059393 ----------------------------------------------------------- -bushfire 38 5 5 38703.789699 444.618237 -Scores: - PC1 PC2 PC3 PC4 PC5 -1 155.972 1.08098 -23.31135 -1.93015 1.218941 -2 157.738 0.35648 -20.95658 -2.42375 0.466415 -3 150.667 2.12545 -16.20395 -2.00140 -0.582924 -4 133.892 5.25124 -15.88873 -2.78469 -0.275261 -5 102.462 13.00611 -21.54096 -4.69409 -0.944176 -6 77.694 18.75377 -28.71865 -6.44244 0.446350 -7 286.266 -11.36184 -98.67134 10.95233 -3.625338 -8 326.627 29.92767 -112.60824 -29.26330 -13.710094 -9 327.898 32.39553 -113.34314 -31.65905 -13.830781 -10 325.131 5.81628 -105.58927 -13.45695 -8.987971 -11 326.458 -7.84562 -94.25242 -6.11547 -8.572845 -12 333.171 -37.69907 -50.89207 8.98187 -1.742979 -13 279.789 -40.78415 -8.06209 7.65884 0.181748 -14 37.714 10.54231 13.46530 -1.55051 2.102662 -15 -90.034 34.68964 18.98186 0.69260 0.417573 -16 -46.492 23.65086 10.07282 4.36090 -0.748517 -17 -43.990 20.36443 9.61049 2.83084 -0.127983 -18 -32.938 19.11199 2.64850 2.92879 -1.473988 -19 -36.555 20.60142 2.01879 0.63832 -1.235075 -20 -46.837 19.89630 6.65142 0.89120 0.271108 -21 -28.670 15.29534 6.59311 3.29638 0.402194 -22 -20.331 15.06559 7.33721 2.16591 2.006327 -23 108.644 -7.92707 -1.45130 6.27388 0.356715 -24 163.697 -16.15568 0.61663 4.24231 0.464415 -25 100.471 -0.30739 0.87762 2.86452 -0.692735 -26 106.922 0.90864 -1.91436 2.54557 -0.565023 -27 121.966 -3.29641 4.85626 -0.47676 -0.490047 -28 98.650 -4.51455 16.64160 -3.08996 -0.839397 -29 88.795 -10.85457 30.46708 -5.37360 0.315657 -30 142.981 -27.89100 22.40713 -1.67126 -0.680158 -31 14.125 -21.60028 29.80480 -8.25272 -0.019693 -32 -244.044 -11.76430 24.53390 -12.52294 2.022312 -33 -283.842 -13.21931 -6.23565 -2.63367 -0.080728 -34 -280.168 -13.41903 -7.69318 -1.24571 -0.722513 -35 -285.666 -13.78452 -6.50318 -1.23756 1.074669 -36 -282.938 -13.82281 -7.63902 0.20435 -0.971673 -37 -281.129 -16.20408 -8.57154 1.85797 0.234486 -38 -282.589 -16.91969 -8.36010 2.35589 0.490630 -------------- -Call: -PcaHubert(x = x, k = p) - -Standard deviations: -[1] 196.7328 21.0860 18.0481 4.4044 1.0324 ----------------------------------------------------------- -========================================================== -> dodata(method="hubert") - -Call: dodata(method = "hubert") -Data Set n p k e1 e2 -========================================================== -heart 12 2 1 546.354097 NA -Scores: - PC1 -1 13.2197 -2 69.9817 -3 6.6946 -4 2.8899 -5 24.9956 -6 -8.9203 -7 12.0121 -8 -24.1915 -9 4.2721 -10 -22.8289 -11 -8.1433 -12 54.6519 -------------- -Call: -PcaHubert(x = x, mcd = FALSE) - -Standard deviations: -[1] 23.374 ----------------------------------------------------------- -starsCYG 47 2 1 0.308922 NA -Scores: - PC1 -1 0.224695 -2 0.758653 -3 -0.089113 -4 0.758653 -5 0.173934 -6 0.466195 -7 -0.433154 -8 0.296411 -9 0.542517 -10 0.116133 -11 0.576303 -12 0.451490 -13 0.429942 -14 -0.997904 -15 -0.745515 -16 -0.408745 -17 -1.071002 -18 -0.803514 -19 -0.834141 -20 0.734210 -21 -0.627085 -22 -0.784992 -23 -0.566652 -24 -0.130992 -25 0.019053 -26 -0.329791 -27 -0.350747 -28 -0.099378 -29 -0.628499 -30 0.890506 -31 -0.573100 -32 0.127022 -33 0.227721 -34 1.128979 -35 -0.676234 -36 0.649894 -37 0.122186 -38 0.227721 -39 0.201140 -40 0.569920 -41 -0.375716 -42 0.069814 -43 0.354212 -44 0.346152 -45 0.559656 -46 -0.009140 -47 -0.487699 -------------- -Call: -PcaHubert(x = x, mcd = FALSE) - -Standard deviations: -[1] 0.55581 ----------------------------------------------------------- -phosphor 18 2 1 215.172048 NA -Scores: - PC1 -1 1.12634 -2 -22.10340 -3 -23.49216 -4 -13.45927 -5 -18.60808 -6 11.24086 -7 -0.14748 -8 -9.77075 -9 -10.37022 -10 12.71798 -11 -4.61857 -12 10.07037 -13 13.16767 -14 7.57254 -15 17.81362 -16 -11.08799 -17 21.70358 -18 18.24496 -------------- -Call: -PcaHubert(x = x, mcd = FALSE) - -Standard deviations: -[1] 14.669 ----------------------------------------------------------- -stackloss 21 3 2 92.695059 22.692615 -Scores: - PC1 PC2 -1 -20.334936 10.28081 -2 -19.772121 11.10736 -3 -16.461573 6.43794 -4 -4.258672 1.73213 -5 -3.773146 1.41928 -6 -4.015909 1.57571 -7 -7.635560 -3.22715 -8 -7.635560 -3.22715 -9 -0.855388 -0.58707 -10 4.298129 4.41664 -11 -0.767202 -3.02229 -12 0.038375 -2.35217 -13 3.172500 2.76354 -14 -3.261224 -6.17206 -15 5.553840 -7.34784 -16 7.242284 -4.86820 -17 14.878925 6.85989 -18 10.939223 1.07406 -19 10.133645 0.40394 -20 4.267234 1.99501 -21 -11.859921 2.12579 -------------- -Call: -PcaHubert(x = x, mcd = FALSE) - -Standard deviations: -[1] 9.6278 4.7637 ----------------------------------------------------------- -salinity 28 3 2 9.897101 7.246198 -Scores: - PC1 PC2 -1 2.858444 1.04359 -2 3.807704 1.55974 -3 6.220733 -4.32114 -4 6.388841 -2.83649 -5 6.077450 -3.70092 -6 5.974494 -0.67230 -7 4.531584 0.78322 -8 2.725849 2.41297 -9 0.100501 -2.13615 -10 -2.358003 -1.49718 -11 -1.317688 -1.15391 -12 0.434635 0.58230 -13 0.116019 1.79022 -14 -1.771501 2.71749 -15 -2.630757 -2.44003 -16 2.289743 -5.51829 -17 0.637985 -1.26452 -18 3.076147 0.19883 -19 0.097381 -1.95868 -20 -1.572471 -0.93003 -21 -1.284185 2.21858 -22 -2.531713 3.30313 -23 -3.865359 -3.01230 -24 -2.143461 -2.41918 -25 -0.714414 -0.41227 -26 -1.327781 1.18373 -27 -2.201166 2.41566 -28 -2.931988 3.20536 -------------- -Call: -PcaHubert(x = x, mcd = FALSE) - -Standard deviations: -[1] 3.1460 2.6919 ----------------------------------------------------------- -hbk 75 3 3 1.966655 1.617943 -Scores: - PC1 PC2 PC3 -1 31.105415 -4.714217 -10.4566165 -2 31.707650 -5.748724 -10.7682402 -3 33.366131 -4.625897 -12.1570167 -4 34.173377 -6.069657 -12.4466895 -5 33.780418 -5.508823 -11.9872893 -6 32.493478 -4.684595 -10.5679819 -7 32.592637 -5.235522 -10.3765493 -8 31.293363 -4.865797 -10.9379676 -9 33.160964 -5.714260 -12.3098920 -10 31.919786 -5.384537 -12.3374332 -11 38.231962 -6.810641 -13.5994385 -12 39.290479 -5.393906 -15.2942554 -13 39.418445 -7.326461 -11.5194898 -14 43.906584 -13.214819 -8.3282743 -15 1.906326 0.716061 0.8635112 -16 0.263255 0.926016 1.9009292 -17 -1.776489 -1.072332 0.5496140 -18 0.464648 0.702441 -0.0482897 -19 0.267826 -1.283779 0.2925812 -20 2.122108 0.165970 0.8924686 -21 0.937217 0.548532 0.4132196 -22 0.423273 -1.781869 0.0323061 -23 0.047532 0.018909 1.1259327 -24 -0.490041 -0.520202 1.1065753 -25 -2.143049 0.720869 0.0495474 -26 1.094748 -1.459175 -0.2226246 -27 2.070705 0.898573 -0.0023229 -28 -0.294998 0.830258 -0.5929001 -29 -1.242995 0.300216 0.2010507 -30 0.147958 0.439099 -2.0003038 -31 0.170818 1.440946 0.9755627 -32 -0.958531 -1.199730 1.0129867 -33 0.697307 -0.874343 0.7260649 -34 -2.278946 0.261106 -0.4196544 -35 1.962829 0.809318 -0.2033113 -36 0.626631 -0.600666 -0.8004036 -37 0.550885 -1.881448 -0.7382776 -38 -1.249717 0.336214 0.9349845 -39 -1.106696 1.569418 -0.1869576 -40 -0.684034 -0.939963 0.1034965 -41 1.559314 1.551408 -0.3660323 -42 -0.538741 -0.447358 -1.6361099 -43 -0.252685 -2.080564 0.7765259 -44 0.217012 1.027281 -1.7015154 -45 -1.497600 1.349234 0.2698932 -46 0.100388 1.026443 -1.5390401 -47 -0.811117 2.195271 0.5208141 -48 1.462210 1.321318 -0.5600144 -49 1.383976 0.740714 0.7348906 -50 1.636773 -0.215464 -0.3195369 -51 -0.530918 0.759743 1.2069247 -52 -0.109566 2.107455 0.5315473 -53 -0.564334 -0.060847 -2.3910630 -54 -0.272234 -1.122711 1.5060028 -55 -0.608660 -1.197219 0.5255609 -56 0.565430 -0.710345 1.3708230 -57 -1.115629 0.888816 0.4186014 -58 1.351288 -0.374815 1.1980618 -59 0.998016 -0.151228 -0.9007970 -60 0.124017 -0.764846 -1.9005963 -61 1.189858 -1.905264 -0.7721322 -62 -2.190589 0.579614 0.1377914 -63 -0.518278 -0.931130 1.4534768 -64 2.124566 0.194391 0.0327092 -65 0.154218 1.050861 -1.1309885 -66 -1.197852 -1.044147 0.2265269 -67 -0.114174 -0.094763 0.5168926 -68 -2.201115 0.032271 -0.8573493 -69 -1.307843 1.104815 0.7741270 -70 0.691449 -0.676665 -1.0004603 -71 1.150975 0.050861 0.0717068 -72 -0.457293 -0.861871 -0.1026350 -73 -0.392258 -0.897451 -0.9178065 -74 -0.584658 -1.450471 -0.3201857 -75 -0.972517 -0.063777 -1.8223995 -------------- -Call: -PcaHubert(x = x, mcd = FALSE) - -Standard deviations: -[1] 1.4024 1.2720 1.1801 ----------------------------------------------------------- -milk 86 8 2 7.629557 3.124392 -Scores: - PC1 PC2 -1 -5.768003 -0.9174359 -2 -6.664422 0.0280812 -3 -0.484521 1.7923710 -4 -5.211590 2.0747301 -5 1.422641 -0.3268437 -6 -1.810360 -0.5469828 -7 -2.402924 -0.1987041 -8 -2.553389 -0.4963662 -9 1.583399 2.5410448 -10 3.267946 0.9141367 -11 9.924771 0.6501301 -12 13.628569 -2.3009846 -13 10.774550 -1.1628697 -14 12.716376 -1.0670330 -15 11.176408 0.7403371 -16 3.209269 -0.0804317 -17 1.256577 2.8931153 -18 2.468720 -1.2008647 -19 2.253229 0.8379608 -20 0.021073 1.6394221 -21 3.205298 -2.3518286 -22 1.470733 -0.9618655 -23 0.475732 -1.7044535 -24 0.930144 -1.3288398 -25 4.151553 -2.2882554 -26 1.314488 -1.3527439 -27 3.613405 -0.0813605 -28 -1.909178 -3.6473200 -29 -3.987263 -1.3255834 -30 -0.370601 -1.5855086 -31 -1.273254 -2.1892809 -32 -0.816634 -0.4514478 -33 -1.553394 -0.2792004 -34 -0.275027 0.6359374 -35 0.980782 -2.2353223 -36 -3.678470 -1.3459182 -37 -0.327102 -2.5615283 -38 -1.563492 -2.2008288 -39 1.876146 -1.0292641 -40 -3.204182 1.6694332 -41 -3.561892 -1.5844770 -42 -6.175135 1.0123714 -43 -2.736601 -0.7040261 -44 -4.981783 0.2434304 -45 0.368802 -0.5011413 -46 0.369508 -1.9511091 -47 -2.306673 -0.0089446 -48 0.215195 -1.1000357 -49 2.704678 -0.5919929 -50 -2.930879 2.7161936 -51 1.846250 0.3732500 -52 5.661288 -0.3139157 -53 1.154929 -0.0575094 -54 0.625715 -0.0733934 -55 -0.453714 -0.7535924 -56 0.343722 0.6460318 -57 1.743002 0.0794685 -58 0.433705 -1.3500731 -59 2.078550 1.0860506 -60 1.867913 0.7162287 -61 0.392645 1.6184583 -62 -1.958732 2.0993596 -63 -2.383251 -0.0253919 -64 -2.383251 -0.0253919 -65 0.780239 2.9018927 -66 2.785329 1.0142893 -67 0.131210 1.2703167 -68 1.110073 1.8140467 -69 1.076878 0.6954148 -70 -3.260160 -5.6233069 -71 2.647036 1.6892084 -72 -2.017340 0.5353349 -73 2.247524 2.6406249 -74 11.649291 -0.7374197 -75 0.280544 2.2306959 -76 1.791213 0.1796005 -77 8.730344 0.3412271 -78 -0.987405 1.3467910 -79 0.560808 0.5006661 -80 3.897879 -1.5270179 -81 -0.792759 -0.8649399 -82 -2.493611 1.6796838 -83 -2.245966 0.1889555 -84 -0.468812 -0.5359088 -85 -0.538372 2.4105954 -86 -0.185347 -1.0176989 -------------- -Call: -PcaHubert(x = x, mcd = FALSE) - -Standard deviations: -[1] 2.7622 1.7676 ----------------------------------------------------------- -bushfire 38 5 1 38435.075910 NA -Scores: - PC1 -1 -111.9345 -2 -113.4128 -3 -105.8364 -4 -89.1684 -5 -58.7216 -6 -35.0370 -7 -250.2123 -8 -292.6877 -9 -294.0765 -10 -290.0193 -11 -289.8168 -12 -290.8645 -13 -232.6865 -14 9.8483 -15 137.1924 -16 92.9804 -17 90.4493 -18 78.6325 -19 82.1178 -20 92.9044 -21 74.9157 -22 66.7350 -23 -62.1981 -24 -116.5696 -25 -53.8907 -26 -60.6384 -27 -74.7621 -28 -50.2202 -29 -38.7483 -30 -93.3887 -31 35.3096 -32 290.8493 -33 326.7236 -34 322.9095 -35 328.5307 -36 325.6791 -37 323.8136 -38 325.2991 -------------- -Call: -PcaHubert(x = x, mcd = FALSE) - -Standard deviations: -[1] 196.05 ----------------------------------------------------------- -========================================================== -> -> ##dodata(method="locantore") -> ##dodata(method="cov") -> -> ## VT::14.11.2018 - commented out - on some platforms PcaHubert will hoose only 1 PC -> ## and will show difference -> ## test.case.1() -> test.case.2() -[1] TRUE -[1] TRUE -[1] TRUE -[1] TRUE -[1] TRUE -[1] TRUE -[1] TRUE -[1] TRUE -[1] TRUE -[1] TRUE -> -> proc.time() - user system elapsed - 1.57 0.20 1.76 +> +> dodata(method="classic") + +Call: dodata(method = "classic") +Data Set n p k e1 e2 +========================================================== +heart 12 2 2 812.379735 9.084962 +Scores: + PC1 PC2 +1 2.7072 1.46576 +2 59.9990 -1.43041 +3 -3.5619 -1.54067 +4 -7.7696 2.52687 +5 14.7660 -0.95822 +6 -20.0489 6.91079 +7 1.4189 2.25961 +8 -34.3308 -4.23717 +9 -6.0487 -0.97859 +10 -33.0102 -3.73143 +11 -18.6372 0.25821 +12 44.5163 -0.54476 +------------- +Call: +PcaClassic(x = x) + +Standard deviations: +[1] 28.5023 3.0141 +---------------------------------------------------------- +starsCYG 47 2 2 0.331279 0.079625 +Scores: + PC1 PC2 +1 0.2072999 0.089973 +2 0.6855999 0.349644 +3 -0.0743007 -0.061028 +4 0.6855999 0.349644 +5 0.1775161 0.015053 +6 0.4223986 0.211351 +7 -0.2926077 -0.516156 +8 0.2188453 0.293607 +9 0.5593696 0.028761 +10 0.0983878 0.074540 +11 0.8258140 -0.711176 +12 0.4167063 0.180244 +13 0.3799883 0.225541 +14 -0.9105236 -0.432014 +15 -0.7418831 -0.125322 +16 -0.4432862 0.048287 +17 -1.0503005 -0.229623 +18 -0.8393302 -0.007831 +19 -0.8126742 -0.195952 +20 0.9842316 -0.688729 +21 -0.6230699 -0.108486 +22 -0.7814875 -0.130933 +23 -0.6017038 0.025840 +24 -0.1857772 0.155474 +25 -0.0020261 0.070412 +26 -0.3640775 0.059510 +27 -0.3458392 -0.069204 +28 -0.1208393 0.053577 +29 -0.6033482 -0.176391 +30 1.1440521 -0.676183 +31 -0.5960920 -0.013765 +32 0.0519296 0.259855 +33 0.1861752 0.167779 +34 1.3802755 -0.632611 +35 -0.6542566 -0.173505 +36 0.5583690 0.392215 +37 0.0561384 0.230152 +38 0.1861752 0.167779 +39 0.1353472 0.241376 +40 0.5355195 0.197080 +41 -0.3980701 0.014294 +42 0.0277576 0.145332 +43 0.2979736 0.234120 +44 0.3049884 0.184614 +45 0.4889809 0.311684 +46 -0.0514512 0.134108 +47 -0.5224950 0.037063 +------------- +Call: +PcaClassic(x = x) + +Standard deviations: +[1] 0.57557 0.28218 +---------------------------------------------------------- +phosphor 18 2 2 220.403422 68.346121 +Scores: + PC1 PC2 +1 4.04290 -15.3459 +2 -22.30489 -1.0004 +3 -24.52683 3.2836 +4 -12.54839 -6.0848 +5 -19.37044 2.2979 +6 15.20366 -19.9424 +7 0.44222 -3.1379 +8 -10.64042 3.6933 +9 -11.67967 5.9670 +10 14.26805 -7.0221 +11 -4.98832 1.5268 +12 8.74986 7.9379 +13 12.26290 6.0251 +14 6.27607 7.5768 +15 17.53246 3.1560 +16 -10.17024 -5.8994 +17 21.05826 5.4492 +18 16.39281 11.5191 +------------- +Call: +PcaClassic(x = x) + +Standard deviations: +[1] 14.8460 8.2672 +---------------------------------------------------------- +stackloss 21 3 3 99.576089 19.581136 +Scores: + PC1 PC2 PC3 +1 20.15352 -4.359452 0.324585 +2 19.81554 -5.300468 0.308294 +3 15.45222 -1.599136 -0.203125 +4 2.40370 -0.145282 2.370302 +5 1.89538 0.070566 0.448061 +6 2.14954 -0.037358 1.409182 +7 4.43153 5.500810 2.468051 +8 4.43153 5.500810 2.468051 +9 -1.47521 1.245404 2.511773 +10 -5.11183 -4.802083 -2.407870 +11 -2.07009 3.667055 -2.261247 +12 -2.66223 2.833964 -3.238659 +13 -4.43589 -2.920053 -2.375287 +14 -0.46404 7.323193 -1.234961 +15 -9.31959 6.232579 -0.056064 +16 -10.33350 3.409533 -0.104938 +17 -14.81094 -9.872607 0.628103 +18 -12.44514 -3.285499 0.742143 +19 -11.85300 -2.452408 1.719555 +20 -5.73994 -2.494520 0.098250 +21 9.98843 1.484952 -3.614198 +------------- +Call: +PcaClassic(x = x) + +Standard deviations: +[1] 9.9788 4.4251 1.8986 +---------------------------------------------------------- +salinity 28 3 3 11.410736 7.075409 +Scores: + PC1 PC2 PC3 +1 -0.937789 -2.40535 0.812909 +2 -1.752631 -2.57774 2.004437 +3 -6.509364 -0.78762 -1.821906 +4 -5.619847 -2.41333 -1.586891 +5 -7.268242 1.61012 1.563568 +6 -4.316558 -3.20411 0.029376 +7 -2.379545 -3.32371 0.703101 +8 0.013514 -3.50586 1.260502 +9 0.265262 -0.16736 -2.886883 +10 1.890755 2.43623 -0.986832 +11 0.804196 2.56656 0.387577 +12 0.935082 -1.03559 -0.074081 +13 1.814839 -1.61087 0.612290 +14 3.407535 -0.15880 2.026088 +15 1.731273 2.95159 -1.840286 +16 -6.129708 7.21368 2.632273 +17 -0.645124 1.06260 0.028697 +18 -1.307532 -2.54679 -0.280273 +19 0.483455 -0.55896 -3.097281 +20 2.053267 0.47308 -1.858703 +21 3.277664 -1.31002 0.453753 +22 4.631644 -0.78005 1.519894 +23 1.864403 5.32790 -0.849694 +24 0.623899 4.29317 0.056461 +25 1.301696 0.37871 -0.646220 +26 2.852126 -0.79527 -0.347711 +27 4.134051 -0.92756 0.449222 +28 4.781679 -0.20467 1.736616 +------------- +Call: +PcaClassic(x = x) + +Standard deviations: +[1] 3.3780 2.6600 1.4836 +---------------------------------------------------------- +hbk 75 3 3 216.162129 1.981077 +Scores: + PC1 PC2 PC3 +1 26.2072 -0.660756 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0.19573429 0.17585482 +[8] 0.00059393 +---------------------------------------------------------- +bushfire 38 5 5 38703.789699 444.618237 +Scores: + PC1 PC2 PC3 PC4 PC5 +1 155.972 1.08098 -23.31135 -1.93015 1.218941 +2 157.738 0.35648 -20.95658 -2.42375 0.466415 +3 150.667 2.12545 -16.20395 -2.00140 -0.582924 +4 133.892 5.25124 -15.88873 -2.78469 -0.275261 +5 102.462 13.00611 -21.54096 -4.69409 -0.944176 +6 77.694 18.75377 -28.71865 -6.44244 0.446350 +7 286.266 -11.36184 -98.67134 10.95233 -3.625338 +8 326.627 29.92767 -112.60824 -29.26330 -13.710094 +9 327.898 32.39553 -113.34314 -31.65905 -13.830781 +10 325.131 5.81628 -105.58927 -13.45695 -8.987971 +11 326.458 -7.84562 -94.25242 -6.11547 -8.572845 +12 333.171 -37.69907 -50.89207 8.98187 -1.742979 +13 279.789 -40.78415 -8.06209 7.65884 0.181748 +14 37.714 10.54231 13.46530 -1.55051 2.102662 +15 -90.034 34.68964 18.98186 0.69260 0.417573 +16 -46.492 23.65086 10.07282 4.36090 -0.748517 +17 -43.990 20.36443 9.61049 2.83084 -0.127983 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2.35589 0.490630 +------------- +Call: +PcaHubert(x = x, k = p) + +Standard deviations: +[1] 196.7328 21.0860 18.0481 4.4044 1.0324 +---------------------------------------------------------- +========================================================== +> dodata(method="hubert") + +Call: dodata(method = "hubert") +Data Set n p k e1 e2 +========================================================== +heart 12 2 1 546.354097 NA +Scores: + PC1 +1 13.2197 +2 69.9817 +3 6.6946 +4 2.8899 +5 24.9956 +6 -8.9203 +7 12.0121 +8 -24.1915 +9 4.2721 +10 -22.8289 +11 -8.1433 +12 54.6519 +------------- +Call: +PcaHubert(x = x, mcd = FALSE) + +Standard deviations: +[1] 23.374 +---------------------------------------------------------- +starsCYG 47 2 1 0.308922 NA +Scores: + PC1 +1 0.224695 +2 0.758653 +3 -0.089113 +4 0.758653 +5 0.173934 +6 0.466195 +7 -0.433154 +8 0.296411 +9 0.542517 +10 0.116133 +11 0.576303 +12 0.451490 +13 0.429942 +14 -0.997904 +15 -0.745515 +16 -0.408745 +17 -1.071002 +18 -0.803514 +19 -0.834141 +20 0.734210 +21 -0.627085 +22 -0.784992 +23 -0.566652 +24 -0.130992 +25 0.019053 +26 -0.329791 +27 -0.350747 +28 -0.099378 +29 -0.628499 +30 0.890506 +31 -0.573100 +32 0.127022 +33 0.227721 +34 1.128979 +35 -0.676234 +36 0.649894 +37 0.122186 +38 0.227721 +39 0.201140 +40 0.569920 +41 -0.375716 +42 0.069814 +43 0.354212 +44 0.346152 +45 0.559656 +46 -0.009140 +47 -0.487699 +------------- +Call: +PcaHubert(x = x, mcd = FALSE) + +Standard deviations: +[1] 0.55581 +---------------------------------------------------------- +phosphor 18 2 1 215.172048 NA +Scores: + PC1 +1 1.12634 +2 -22.10340 +3 -23.49216 +4 -13.45927 +5 -18.60808 +6 11.24086 +7 -0.14748 +8 -9.77075 +9 -10.37022 +10 12.71798 +11 -4.61857 +12 10.07037 +13 13.16767 +14 7.57254 +15 17.81362 +16 -11.08799 +17 21.70358 +18 18.24496 +------------- +Call: +PcaHubert(x = x, mcd = FALSE) + +Standard deviations: +[1] 14.669 +---------------------------------------------------------- +stackloss 21 3 2 92.695059 22.692615 +Scores: + PC1 PC2 +1 -20.334936 10.28081 +2 -19.772121 11.10736 +3 -16.461573 6.43794 +4 -4.258672 1.73213 +5 -3.773146 1.41928 +6 -4.015909 1.57571 +7 -7.635560 -3.22715 +8 -7.635560 -3.22715 +9 -0.855388 -0.58707 +10 4.298129 4.41664 +11 -0.767202 -3.02229 +12 0.038375 -2.35217 +13 3.172500 2.76354 +14 -3.261224 -6.17206 +15 5.553840 -7.34784 +16 7.242284 -4.86820 +17 14.878925 6.85989 +18 10.939223 1.07406 +19 10.133645 0.40394 +20 4.267234 1.99501 +21 -11.859921 2.12579 +------------- +Call: +PcaHubert(x = x, mcd = FALSE) + +Standard deviations: +[1] 9.6278 4.7637 +---------------------------------------------------------- +salinity 28 3 2 9.897101 7.246198 +Scores: + PC1 PC2 +1 2.858444 1.04359 +2 3.807704 1.55974 +3 6.220733 -4.32114 +4 6.388841 -2.83649 +5 6.077450 -3.70092 +6 5.974494 -0.67230 +7 4.531584 0.78322 +8 2.725849 2.41297 +9 0.100501 -2.13615 +10 -2.358003 -1.49718 +11 -1.317688 -1.15391 +12 0.434635 0.58230 +13 0.116019 1.79022 +14 -1.771501 2.71749 +15 -2.630757 -2.44003 +16 2.289743 -5.51829 +17 0.637985 -1.26452 +18 3.076147 0.19883 +19 0.097381 -1.95868 +20 -1.572471 -0.93003 +21 -1.284185 2.21858 +22 -2.531713 3.30313 +23 -3.865359 -3.01230 +24 -2.143461 -2.41918 +25 -0.714414 -0.41227 +26 -1.327781 1.18373 +27 -2.201166 2.41566 +28 -2.931988 3.20536 +------------- +Call: +PcaHubert(x = x, mcd = FALSE) + +Standard deviations: +[1] 3.1460 2.6919 +---------------------------------------------------------- +hbk 75 3 3 1.966655 1.617943 +Scores: + PC1 PC2 PC3 +1 31.105415 -4.714217 -10.4566165 +2 31.707650 -5.748724 -10.7682402 +3 33.366131 -4.625897 -12.1570167 +4 34.173377 -6.069657 -12.4466895 +5 33.780418 -5.508823 -11.9872893 +6 32.493478 -4.684595 -10.5679819 +7 32.592637 -5.235522 -10.3765493 +8 31.293363 -4.865797 -10.9379676 +9 33.160964 -5.714260 -12.3098920 +10 31.919786 -5.384537 -12.3374332 +11 38.231962 -6.810641 -13.5994385 +12 39.290479 -5.393906 -15.2942554 +13 39.418445 -7.326461 -11.5194898 +14 43.906584 -13.214819 -8.3282743 +15 1.906326 0.716061 0.8635112 +16 0.263255 0.926016 1.9009292 +17 -1.776489 -1.072332 0.5496140 +18 0.464648 0.702441 -0.0482897 +19 0.267826 -1.283779 0.2925812 +20 2.122108 0.165970 0.8924686 +21 0.937217 0.548532 0.4132196 +22 0.423273 -1.781869 0.0323061 +23 0.047532 0.018909 1.1259327 +24 -0.490041 -0.520202 1.1065753 +25 -2.143049 0.720869 0.0495474 +26 1.094748 -1.459175 -0.2226246 +27 2.070705 0.898573 -0.0023229 +28 -0.294998 0.830258 -0.5929001 +29 -1.242995 0.300216 0.2010507 +30 0.147958 0.439099 -2.0003038 +31 0.170818 1.440946 0.9755627 +32 -0.958531 -1.199730 1.0129867 +33 0.697307 -0.874343 0.7260649 +34 -2.278946 0.261106 -0.4196544 +35 1.962829 0.809318 -0.2033113 +36 0.626631 -0.600666 -0.8004036 +37 0.550885 -1.881448 -0.7382776 +38 -1.249717 0.336214 0.9349845 +39 -1.106696 1.569418 -0.1869576 +40 -0.684034 -0.939963 0.1034965 +41 1.559314 1.551408 -0.3660323 +42 -0.538741 -0.447358 -1.6361099 +43 -0.252685 -2.080564 0.7765259 +44 0.217012 1.027281 -1.7015154 +45 -1.497600 1.349234 0.2698932 +46 0.100388 1.026443 -1.5390401 +47 -0.811117 2.195271 0.5208141 +48 1.462210 1.321318 -0.5600144 +49 1.383976 0.740714 0.7348906 +50 1.636773 -0.215464 -0.3195369 +51 -0.530918 0.759743 1.2069247 +52 -0.109566 2.107455 0.5315473 +53 -0.564334 -0.060847 -2.3910630 +54 -0.272234 -1.122711 1.5060028 +55 -0.608660 -1.197219 0.5255609 +56 0.565430 -0.710345 1.3708230 +57 -1.115629 0.888816 0.4186014 +58 1.351288 -0.374815 1.1980618 +59 0.998016 -0.151228 -0.9007970 +60 0.124017 -0.764846 -1.9005963 +61 1.189858 -1.905264 -0.7721322 +62 -2.190589 0.579614 0.1377914 +63 -0.518278 -0.931130 1.4534768 +64 2.124566 0.194391 0.0327092 +65 0.154218 1.050861 -1.1309885 +66 -1.197852 -1.044147 0.2265269 +67 -0.114174 -0.094763 0.5168926 +68 -2.201115 0.032271 -0.8573493 +69 -1.307843 1.104815 0.7741270 +70 0.691449 -0.676665 -1.0004603 +71 1.150975 0.050861 0.0717068 +72 -0.457293 -0.861871 -0.1026350 +73 -0.392258 -0.897451 -0.9178065 +74 -0.584658 -1.450471 -0.3201857 +75 -0.972517 -0.063777 -1.8223995 +------------- +Call: +PcaHubert(x = x, mcd = FALSE) + +Standard deviations: +[1] 1.4024 1.2720 1.1801 +---------------------------------------------------------- +milk 86 8 2 7.629557 3.124392 +Scores: + PC1 PC2 +1 -5.768003 -0.9174359 +2 -6.664422 0.0280812 +3 -0.484521 1.7923710 +4 -5.211590 2.0747301 +5 1.422641 -0.3268437 +6 -1.810360 -0.5469828 +7 -2.402924 -0.1987041 +8 -2.553389 -0.4963662 +9 1.583399 2.5410448 +10 3.267946 0.9141367 +11 9.924771 0.6501301 +12 13.628569 -2.3009846 +13 10.774550 -1.1628697 +14 12.716376 -1.0670330 +15 11.176408 0.7403371 +16 3.209269 -0.0804317 +17 1.256577 2.8931153 +18 2.468720 -1.2008647 +19 2.253229 0.8379608 +20 0.021073 1.6394221 +21 3.205298 -2.3518286 +22 1.470733 -0.9618655 +23 0.475732 -1.7044535 +24 0.930144 -1.3288398 +25 4.151553 -2.2882554 +26 1.314488 -1.3527439 +27 3.613405 -0.0813605 +28 -1.909178 -3.6473200 +29 -3.987263 -1.3255834 +30 -0.370601 -1.5855086 +31 -1.273254 -2.1892809 +32 -0.816634 -0.4514478 +33 -1.553394 -0.2792004 +34 -0.275027 0.6359374 +35 0.980782 -2.2353223 +36 -3.678470 -1.3459182 +37 -0.327102 -2.5615283 +38 -1.563492 -2.2008288 +39 1.876146 -1.0292641 +40 -3.204182 1.6694332 +41 -3.561892 -1.5844770 +42 -6.175135 1.0123714 +43 -2.736601 -0.7040261 +44 -4.981783 0.2434304 +45 0.368802 -0.5011413 +46 0.369508 -1.9511091 +47 -2.306673 -0.0089446 +48 0.215195 -1.1000357 +49 2.704678 -0.5919929 +50 -2.930879 2.7161936 +51 1.846250 0.3732500 +52 5.661288 -0.3139157 +53 1.154929 -0.0575094 +54 0.625715 -0.0733934 +55 -0.453714 -0.7535924 +56 0.343722 0.6460318 +57 1.743002 0.0794685 +58 0.433705 -1.3500731 +59 2.078550 1.0860506 +60 1.867913 0.7162287 +61 0.392645 1.6184583 +62 -1.958732 2.0993596 +63 -2.383251 -0.0253919 +64 -2.383251 -0.0253919 +65 0.780239 2.9018927 +66 2.785329 1.0142893 +67 0.131210 1.2703167 +68 1.110073 1.8140467 +69 1.076878 0.6954148 +70 -3.260160 -5.6233069 +71 2.647036 1.6892084 +72 -2.017340 0.5353349 +73 2.247524 2.6406249 +74 11.649291 -0.7374197 +75 0.280544 2.2306959 +76 1.791213 0.1796005 +77 8.730344 0.3412271 +78 -0.987405 1.3467910 +79 0.560808 0.5006661 +80 3.897879 -1.5270179 +81 -0.792759 -0.8649399 +82 -2.493611 1.6796838 +83 -2.245966 0.1889555 +84 -0.468812 -0.5359088 +85 -0.538372 2.4105954 +86 -0.185347 -1.0176989 +------------- +Call: +PcaHubert(x = x, mcd = FALSE) + +Standard deviations: +[1] 2.7622 1.7676 +---------------------------------------------------------- +bushfire 38 5 1 38435.075910 NA +Scores: + PC1 +1 -111.9345 +2 -113.4128 +3 -105.8364 +4 -89.1684 +5 -58.7216 +6 -35.0370 +7 -250.2123 +8 -292.6877 +9 -294.0765 +10 -290.0193 +11 -289.8168 +12 -290.8645 +13 -232.6865 +14 9.8483 +15 137.1924 +16 92.9804 +17 90.4493 +18 78.6325 +19 82.1178 +20 92.9044 +21 74.9157 +22 66.7350 +23 -62.1981 +24 -116.5696 +25 -53.8907 +26 -60.6384 +27 -74.7621 +28 -50.2202 +29 -38.7483 +30 -93.3887 +31 35.3096 +32 290.8493 +33 326.7236 +34 322.9095 +35 328.5307 +36 325.6791 +37 323.8136 +38 325.2991 +------------- +Call: +PcaHubert(x = x, mcd = FALSE) + +Standard deviations: +[1] 196.05 +---------------------------------------------------------- +========================================================== +> +> dodata(method="locantore") + +Call: dodata(method = "locantore") +Data Set n p k e1 e2 +========================================================== +heart 12 2 2 1.835912 0.084745 +Scores: + PC1 PC2 + [1,] 7.3042 1.745289 + [2,] 64.6474 0.164425 + [3,] 1.1057 -1.404189 + [4,] -3.1943 2.565728 + [5,] 19.4154 -0.401369 + [6,] -15.5709 6.666752 + [7,] 5.9980 2.509372 + [8,] -29.5933 -4.805972 + [9,] -1.3933 -0.899323 +[10,] -28.2845 -4.270057 +[11,] -14.0069 0.048311 +[12,] 49.1484 0.694598 +------------- +Call: +PcaLocantore(x = x) + +Standard deviations: +[1] 1.35496 0.29111 +---------------------------------------------------------- +starsCYG 47 2 2 0.779919 0.050341 +Scores: + PC1 PC2 + [1,] 0.174291 -0.0489127 + [2,] 0.703776 0.0769650 + [3,] -0.136954 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-0.1269568 2.9497e-04 +[80,] 0.2903958 7.8932e-04 +[81,] 0.0979443 -3.1531e-04 +[82,] -0.0548155 4.2140e-04 +[83,] -0.0371550 -5.6653e-04 +[84,] -0.0835149 -7.0682e-04 +[85,] 0.1864954 1.0604e-03 +[86,] 0.1074252 -7.4859e-04 +------------- +Call: +PcaLocantore(x = x) + +Standard deviations: +[1] 1.08405293 0.65307452 0.28970076 0.11162824 0.09072195 0.06659711 0.05888048 +[8] 0.00022877 +---------------------------------------------------------- +bushfire 38 5 5 1.464779 0.043290 +Scores: + PC1 PC2 PC3 PC4 PC5 + [1,] -69.9562 -13.0364 0.98678 1.054123 2.411188 + [2,] -71.5209 -10.5459 0.31081 1.631208 1.663470 + [3,] -63.9308 -7.4622 -2.43241 0.671038 0.465836 + [4,] -47.0413 -9.6343 -3.83609 0.758349 0.683983 + [5,] -15.9088 -20.1737 -5.55893 1.181744 -0.053563 + [6,] 8.3484 -30.7646 -5.51541 1.877227 1.338037 + [7,] -207.7458 -66.2492 34.48519 -5.894885 -1.051729 + [8,] -246.4327 -97.0433 -9.57057 22.286225 -9.234869 + [9,] -247.5984 -98.8613 -12.13406 23.948770 -9.250401 +[10,] -245.8121 -79.2634 12.47990 13.046128 -5.125478 +[11,] -246.8887 -62.5899 21.21764 9.111011 -5.080985 +[12,] -251.1354 -9.2115 31.77448 0.236379 0.707528 +[13,] -194.0239 27.1288 21.05023 0.940913 1.781359 +[14,] 51.7182 8.5038 -11.22109 -2.132458 1.984807 +[15,] 180.5597 -4.8151 -21.36630 -9.390663 -0.817036 +[16,] 135.7246 -5.0756 -11.33517 -10.015567 -1.670831 +[17,] 133.0151 -4.0344 -8.95540 -7.702087 -0.923277 +[18,] 121.2619 -9.0627 -5.96042 -7.210971 -2.092872 +[19,] 124.9038 -10.6649 -7.22555 -5.349553 -1.771009 +[20,] 135.5410 -6.8146 -7.52834 -5.562769 -0.396924 +[21,] 117.1950 -3.5643 -4.67473 -6.862117 -0.234551 +[22,] 108.9944 -2.3344 -5.90349 -5.928299 1.455538 +[23,] -21.4031 8.0668 6.19525 -4.784890 0.671394 +[24,] -76.3499 16.7804 6.52545 -1.391250 1.219282 +[25,] -12.5732 6.1109 -1.45259 -3.512072 -0.375837 +[26,] -19.1800 3.4685 -2.02243 -3.490028 -0.169127 +[27,] -33.6733 12.0757 -3.53322 0.048666 0.067468 +[28,] -9.3966 21.5055 -5.91671 2.650895 -0.449672 +[29,] 1.4123 35.8559 -5.98222 5.982362 0.613667 +[30,] -54.2683 39.6029 7.82694 6.759994 0.035048 +[31,] 74.8866 34.9048 10.03986 12.592158 0.149308 +[32,] 331.4144 9.3079 27.73391 17.334531 1.015536 +[33,] 367.6915 -19.5135 48.52753 10.213314 -1.268047 +[34,] 363.8686 -20.4079 49.32855 8.986581 -1.930673 +[35,] 369.4371 -19.5074 49.66761 9.001542 -0.179566 +[36,] 366.5850 -20.2555 50.30290 7.745330 -2.259131 +[37,] 364.5463 -19.8198 53.00407 6.757796 -1.083372 +[38,] 365.9709 -19.3753 53.80168 6.467284 -0.854384 +------------- +Call: +PcaLocantore(x = x) + +Standard deviations: +[1] 1.210280 0.208063 0.177790 0.062694 0.014423 +---------------------------------------------------------- +========================================================== +> dodata(method="cov") + +Call: dodata(method = "cov") +Data Set n p k e1 e2 +========================================================== +heart 12 2 2 802.107569 15.354150 +Scores: + PC1 PC2 +1 8.18562 1.17998 +2 65.41185 -2.80723 +3 1.86039 -1.70646 +4 -2.26910 2.44051 +5 20.19603 -1.47331 +6 -14.46264 7.05759 +7 6.91264 1.99823 +8 -28.95436 -3.81624 +9 -0.61523 -1.09711 +10 -27.62427 -3.33575 +11 -13.17788 0.37931 +12 49.94879 -1.62675 +------------- +Call: +PcaCov(x = x) + +Standard deviations: +[1] 28.3215 3.9184 +---------------------------------------------------------- +starsCYG 47 2 2 0.362996 0.009574 +Scores: + PC1 PC2 +1 0.272263 -0.07964458 +2 0.804544 0.03382837 +3 -0.040587 -0.14464760 +4 0.804544 0.03382837 +5 0.222468 -0.14305159 +6 0.512941 -0.02420304 +7 -0.378928 -0.51924735 +8 0.341045 0.11236831 +9 0.592550 -0.23812462 +10 0.163442 -0.06357822 +11 0.638370 -1.02323643 +12 0.498667 -0.05242075 +13 0.476291 0.00142479 +14 -0.947664 -0.26343572 +15 -0.699020 -0.01711057 +16 -0.363464 0.06475681 +17 -1.024352 -0.02972862 +18 -0.759174 0.12317995 +19 -0.786925 -0.06478250 +20 0.796654 -1.04660568 +21 -0.580307 -0.03463751 +22 -0.738591 -0.01126825 +23 -0.521748 0.08812607 +24 -0.086135 0.09457052 +25 0.065975 -0.03907968 +26 -0.284322 0.05307219 +27 -0.303309 -0.07553370 +28 -0.052738 -0.02155274 +29 -0.580638 -0.10534741 +30 0.953478 -1.07986770 +31 -0.527590 0.04855502 +32 0.171408 0.12730538 +33 0.274054 0.00095808 +34 1.192364 -1.10502882 +35 -0.628641 -0.08815176 +36 0.694595 0.11071187 +37 0.167026 0.09762710 +38 0.274054 0.00095808 +39 0.246168 0.08594248 +40 0.617380 -0.06994769 +41 -0.329735 0.01934346 +42 0.115770 0.02432733 +43 0.400071 0.03289494 +44 0.392768 -0.01656886 +45 0.605229 0.05314718 +46 0.036628 0.03601196 +47 -0.442606 0.07644144 +------------- +Call: +PcaCov(x = x) + +Standard deviations: +[1] 0.602491 0.097845 +---------------------------------------------------------- +phosphor 18 2 2 406.415096 31.072588 +Scores: + PC1 PC2 +1 2.7987 -19.015683 +2 -20.4311 -0.032022 +3 -21.8198 4.589809 +4 -11.7869 -6.837833 +5 -16.9357 2.664785 +6 12.9132 -25.602526 +7 1.5249 -6.351664 +8 -8.0984 2.416616 +9 -8.6979 4.843680 +10 14.3903 -12.732868 +11 -2.9462 -0.760656 +12 11.7427 2.991004 +13 14.8400 0.459849 +14 9.2449 3.095095 +15 19.4860 -3.336883 +16 -9.4156 -7.096788 +17 23.3759 -1.737460 +18 19.9173 5.092467 +------------- +Call: +PcaCov(x = x) + +Standard deviations: +[1] 20.1597 5.5743 +---------------------------------------------------------- +stackloss 21 3 3 56.394968 17.878262 +Scores: + PC1 PC2 PC3 + [1,] 10.538448 13.596944 12.84989 + [2,] 9.674846 14.098881 12.89733 + [3,] 8.993255 9.221043 9.94062 + [4,] 1.744427 3.649104 0.17292 + [5,] 0.980215 2.223126 1.34874 + [6,] 1.362321 2.936115 0.76083 + [7,] 6.926040 0.637480 -0.11170 + [8,] 6.926040 0.637480 -0.11170 + [9,] 0.046655 0.977727 -2.46930 +[10,] -7.909092 0.926343 0.80232 +[11,] -0.136672 -3.591094 0.37539 +[12,] -1.382381 -3.802146 1.01074 +[13,] -6.181887 -0.077532 0.70744 +[14,] 3.699843 -4.885854 -0.40226 +[15,] -2.768005 -7.507870 -6.08487 +[16,] -5.358811 -6.002058 -5.94256 +[17,] -17.067135 1.738055 -5.86637 +[18,] -11.021920 -1.775507 -6.19842 +[19,] -9.776212 -1.564455 -6.83377 +[20,] -6.075508 0.369252 -2.08345 +[21,] 6.301743 2.706174 8.79509 +------------- +Call: +PcaCov(x = x) + +Standard deviations: +[1] 7.5097 4.2283 1.8427 +---------------------------------------------------------- +salinity 28 3 3 15.689189 5.266840 +Scores: + PC1 PC2 PC3 +1 -1.59888 1.582157 0.135248 +2 -2.26975 2.429177 1.107832 +3 -6.79543 -2.034636 0.853876 +4 -6.36795 -0.602960 -0.267268 +5 -6.42044 -1.520259 5.022962 +6 -5.13821 1.225470 0.016977 +7 -3.24014 1.998671 -0.123418 +8 -0.93998 2.789889 -0.515656 +9 -0.30856 -2.424345 -1.422752 +10 2.20362 -2.800513 1.142127 +11 1.38120 -2.076832 2.515630 +12 0.44997 0.207439 -0.152835 +13 1.21669 1.193701 -0.277116 +14 3.31664 1.306627 1.213342 +15 2.08484 -3.774814 0.905400 +16 -3.64862 -4.677257 9.046484 +17 -0.46124 -1.411762 1.706719 +18 -2.13038 0.890401 -0.633349 +19 -0.23610 -2.262304 -1.885048 +20 1.70337 -1.970773 -0.781880 +21 2.67273 1.038742 -0.610945 +22 4.24561 1.547290 0.108927 +23 2.99619 -4.785343 3.094945 +24 1.64474 -3.564562 3.432429 +25 1.11703 -1.158030 0.237700 +26 2.30707 0.069668 -0.735809 +27 3.59356 0.860498 -0.611380 +28 4.57550 1.300407 0.589307 +------------- +Call: +PcaCov(x = x) + +Standard deviations: +[1] 3.9610 2.2950 1.0901 +---------------------------------------------------------- +hbk 75 3 3 1.935081 1.591967 +Scores: + PC1 PC2 PC3 +1 31.105415 -4.714217 10.4566165 +2 31.707650 -5.748724 10.7682402 +3 33.366131 -4.625897 12.1570167 +4 34.173377 -6.069657 12.4466895 +5 33.780418 -5.508823 11.9872893 +6 32.493478 -4.684595 10.5679819 +7 32.592637 -5.235522 10.3765493 +8 31.293363 -4.865797 10.9379676 +9 33.160964 -5.714260 12.3098920 +10 31.919786 -5.384537 12.3374332 +11 38.231962 -6.810641 13.5994385 +12 39.290479 -5.393906 15.2942554 +13 39.418445 -7.326461 11.5194898 +14 43.906584 -13.214819 8.3282743 +15 1.906326 0.716061 -0.8635112 +16 0.263255 0.926016 -1.9009292 +17 -1.776489 -1.072332 -0.5496140 +18 0.464648 0.702441 0.0482897 +19 0.267826 -1.283779 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-0.7348906 +50 1.636773 -0.215464 0.3195369 +51 -0.530918 0.759743 -1.2069247 +52 -0.109566 2.107455 -0.5315473 +53 -0.564334 -0.060847 2.3910630 +54 -0.272234 -1.122711 -1.5060028 +55 -0.608660 -1.197219 -0.5255609 +56 0.565430 -0.710345 -1.3708230 +57 -1.115629 0.888816 -0.4186014 +58 1.351288 -0.374815 -1.1980618 +59 0.998016 -0.151228 0.9007970 +60 0.124017 -0.764846 1.9005963 +61 1.189858 -1.905264 0.7721322 +62 -2.190589 0.579614 -0.1377914 +63 -0.518278 -0.931130 -1.4534768 +64 2.124566 0.194391 -0.0327092 +65 0.154218 1.050861 1.1309885 +66 -1.197852 -1.044147 -0.2265269 +67 -0.114174 -0.094763 -0.5168926 +68 -2.201115 0.032271 0.8573493 +69 -1.307843 1.104815 -0.7741270 +70 0.691449 -0.676665 1.0004603 +71 1.150975 0.050861 -0.0717068 +72 -0.457293 -0.861871 0.1026350 +73 -0.392258 -0.897451 0.9178065 +74 -0.584658 -1.450471 0.3201857 +75 -0.972517 -0.063777 1.8223995 +------------- +Call: +PcaCov(x = x) + +Standard deviations: +[1] 1.3911 1.2617 1.1706 +---------------------------------------------------------- +milk 86 8 8 7.282476 2.813536 +Scores: + PC1 PC2 PC3 PC4 PC5 PC6 +1 5.7090867 1.388263 0.0055924 0.3510505 -0.7335114 -1.41950731 +2 6.5825186 0.480410 -1.1356236 -0.3250838 -0.7343177 -1.71595400 +3 0.7433619 -1.749281 0.2510521 0.3450575 0.2996413 -0.34585702 +4 5.5733255 -1.588521 0.8934908 -0.3412408 0.0087626 0.07235942 +5 -1.3030839 0.142394 0.8487785 -0.5847851 0.0588053 -0.08968553 +6 1.7708705 0.674240 -0.4153759 -0.1915734 0.1382138 0.12454293 +7 2.3570866 0.381017 -0.8771357 -0.3739365 0.2918453 0.13437364 +8 2.5700714 0.695006 0.0061108 -0.4323695 0.1643797 -0.00469369 +9 -1.1725766 -2.713291 1.0677483 -0.0647875 0.1183120 -0.10762785 +10 -3.1357225 -1.255175 0.0666017 0.5083690 -0.1096080 -0.00647493 +11 -9.5333894 -1.608943 2.7307809 0.1690156 -0.1682415 -0.06597478 +12 -13.6028505 0.941083 2.0136258 -0.1076520 -0.0475905 -0.15295614 +13 -10.9497471 0.048776 -0.8765307 0.1518572 0.1428294 -0.00064406 +14 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+========================================================== +> ## IGNORE_RDIFF_END +> +> ## VT::14.11.2018 - commented out - on some platforms PcaHubert will choose only 1 PC +> ## and will show difference +> ## test.case.1() +> +> test.case.2() +[1] TRUE +[1] TRUE +[1] TRUE +[1] TRUE +[1] TRUE +[1] TRUE +[1] TRUE +[1] TRUE +[1] TRUE +[1] TRUE +> +> proc.time() + user system elapsed + 3.23 0.68 4.00