r-cran-mice 3.7.0-1 source package in Ubuntu
Changelog
r-cran-mice (3.7.0-1) unstable; urgency=medium * Team upload. * New upstream version -- Dylan Aïssi <email address hidden> Sat, 04 Jan 2020 11:21:58 +0100
Upload details
- Uploaded by:
- Debian R Packages Maintainers
- Uploaded to:
- Sid
- Original maintainer:
- Debian R Packages Maintainers
- Architectures:
- any
- Section:
- misc
- Urgency:
- Medium Urgency
See full publishing history Publishing
| Series | Published | Component | Section |
|---|
Downloads
| File | Size | SHA-256 Checksum |
|---|---|---|
| r-cran-mice_3.7.0-1.dsc | 2.2 KiB | 9195ccd83edb05d59308ba813f4f9f1b3d44b7317759ae11142c57deb7a3a8b1 |
| r-cran-mice_3.7.0.orig.tar.gz | 521.6 KiB | 4eab2959bcfe28eae068e5e697901b47b05a6c88e0a34af8303f1ec05ed0a1f3 |
| r-cran-mice_3.7.0-1.debian.tar.xz | 2.9 KiB | 6f033d40441800fc9d37fb427a09b5b7e4baff469a473ca3369cb54696e84910 |
Available diffs
- diff from 3.6.0-2 to 3.7.0-1 (43.2 KiB)
No changes file available.
Binary packages built by this source
- r-cran-mice: GNU R multivariate imputation by chained equations
Multiple imputation using Fully Conditional Specification (FCS)
implemented by the MICE algorithm as described in Van Buuren and
Groothuis-Oudshoorn (2011) <doi:10. 18637/jss. v045.i03> . Each variable has
its own imputation model. Built-in imputation models are provided for
continuous data (predictive mean matching, normal), binary data (logistic
regression), unordered categorical data (polytomous logistic regression)
and ordered categorical data (proportional odds). MICE can also impute
continuous two-level data (normal model, pan, second-level variables).
Passive imputation can be used to maintain consistency between variables.
Various diagnostic plots are available to inspect the quality of the
imputations.
- r-cran-mice-dbgsym: debug symbols for r-cran-mice
