r-bioc-pcamethods 1.78.0-1build1 source package in Ubuntu

Changelog

r-bioc-pcamethods (1.78.0-1build1) focal; urgency=medium

  * No-change rebuild for libgcc-s1 package name change.

 -- Matthias Klose <email address hidden>  Mon, 23 Mar 2020 07:24:11 +0100

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Uploaded by:
Matthias Klose on 2020-03-23
Uploaded to:
Focal
Original maintainer:
Debian R Packages Maintainers
Architectures:
any
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Focal release on 2020-03-24 universe misc

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r-bioc-pcamethods_1.78.0.orig.tar.gz 686.6 KiB f206999713e6910b43bb893a0ea6e88fd842e0ae18c509dc4b1554e9e63139f2
r-bioc-pcamethods_1.78.0-1build1.debian.tar.xz 2.5 KiB f15c88fc3b88e199a4996b8143fd8923a7b708e1bb5e96632b50bfae40262c30
r-bioc-pcamethods_1.78.0-1build1.dsc 2.1 KiB 623a6a947382d446634b328b421cf9a9e91b0530922bcb4dee913ed1dedddbb2

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Binary packages built by this source

r-bioc-pcamethods: BioConductor collection of PCA methods

 Provides Bayesian PCA, Probabilistic PCA, Nipals PCA,
 Inverse Non-Linear PCA and the conventional SVD PCA. A cluster
 based method for missing value estimation is included for
 comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA
 on incomplete data as well as for accurate missing value
 estimation. A set of methods for printing and plotting the
 results is also provided. All PCA methods make use of the same
 data structure (pcaRes) to provide a common interface to the
 PCA results. Initiated at the Max-Planck Institute for
 Molecular Plant Physiology, Golm, Germany.

r-bioc-pcamethods-dbgsym: debug symbols for r-bioc-pcamethods