r-cran-mice 3.13.0-3 source package in Ubuntu

Changelog

r-cran-mice (3.13.0-3) unstable; urgency=medium

  * Team Upload.
  * d/t/run-unit-test: Do not invoke sed on a
    removed file (Closes: #983765)
  * Bump Standards-Version to 4.6.0 (no changes needed)

 -- Nilesh Patra <email address hidden>  Thu, 21 Oct 2021 15:16:27 +0530

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 Pocket Published Component Section

Downloads

File Size SHA-256 Checksum
r-cran-mice_3.13.0-3.dsc 2.5 KiB 3b8e6f135e8747db08c74ebcfd1f7ac186f939f02f16aeb55ffba4b3efeb1100
r-cran-mice_3.13.0.orig.tar.gz 560.6 KiB 5108e4673512c96ced19c23fdbb0feea2b2a655a4c7dc9afb06a2a1a29f69785
r-cran-mice_3.13.0-3.debian.tar.xz 3.8 KiB c8ca7d54fbfec2fbb18b9cf767a9fa84e3ca57ed4d02a45e1f2c000f59f502a3

Available diffs

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