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elrm

Exact Logistic Regression via MCMC

v1.2.6 · Dec 18, 2024 · GPL (>= 2)
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Description

Implements a Markov Chain Monte Carlo algorithm to approximate exact conditional inference for logistic regression models. Exact conditional inference is based on the distribution of the sufficient statistics for the parameters of interest given the sufficient statistics for the remaining nuisance parameters. Using model formula notation, users specify a logistic model and model terms of interest for exact inference. See Zamar et al. (2007) <doi:10.18637/jss.v021.i03> for more details.

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14 OK
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r-devel-linux-x86_64-debian-clang OK
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
r-oldrel-macos-x86_64 OK
r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
r-release-linux-x86_64 OK
r-release-macos-arm64 OK
r-release-macos-x86_64 OK
r-release-windows-x86_64 OK

Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies coda elrm

Version History

new 1.2.6 Mar 10, 2026
updated 1.2.6 ← 1.2.5 diff Dec 17, 2024
updated 1.2.5 ← 1.2.4 diff Oct 25, 2021
updated 1.2.4 ← 1.2.3 diff Aug 29, 2019
updated 1.2.3 ← 1.2.2 diff Jun 27, 2019
updated 1.2.2 ← 1.2.1 diff Dec 6, 2013
updated 1.2.1 ← 1.2 diff Apr 30, 2010
updated 1.2 ← 1.1.3 diff Jan 25, 2009
updated 1.1.3 ← 1.1.2 diff Nov 1, 2008
updated 1.1.2 ← 1.1.1 diff Oct 14, 2007
updated 1.1.1 ← 1.1 diff Sep 29, 2007
updated 1.1 ← 1.0 diff Feb 10, 2007
new 1.0 Nov 19, 2006