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elrm  

Exact Logistic Regression via MCMC
View on CRAN: Click here


Download and install elrm package within the R console
Install from CRAN:
install.packages("elrm")

Install from Github:
library("remotes")
install_github("cran/elrm")

Install by package version:
library("remotes")
install_version("elrm", "1.2.5")



Attach the package and use:
library("elrm")
Maintained by
David Zamar
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2006-11-20
Latest Update: 2021-10-26
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) for more details.
How to cite:
David Zamar (2006). elrm: Exact Logistic Regression via MCMC. R package version 1.2.5, https://cran.r-project.org/web/packages/elrm
Previous versions and publish date:
1.0 (2006-11-20 09:13), 1.1.1 (2007-09-30 21:12), 1.1.2 (2007-10-15 11:25), 1.1.3 (2008-11-02 19:56), 1.1 (2007-02-11 13:32), 1.2.1 (2010-05-01 19:51), 1.2.2 (2013-12-07 00:52), 1.2.3 (2019-06-28 16:40), 1.2.4 (2019-08-30 23:40), 1.2 (2009-01-26 09:53)
Other packages that cited elrm R package
View elrm citation profile
Other R packages that elrm depends, imports, suggests or enhances
Functions, R codes and Examples using the elrm R package
Some associated functions: crashDat . diabDat . drugDat . elrm . plot.elrm . summary.elrm . titanDat . update.elrm . utiDat . 
Some associated R codes: adjustProb.R . batchSize.R . bm.R . elrm.R . getConfInterval.R . getDesignMatrix.R . getDistTable.R . getJointInf.R . getMarginalInf.R . id.R . plot.elrm.R . progress.R . row.matches.R . summary.elrm.R . update.elrm.R . zzz.R .  Full elrm package functions and examples
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