binomlogit: Efficient MCMC for Binomial Logit Models
Version 1.2

The R package contains different MCMC schemes to estimate the regression coefficients of a binomial (or binary) logit model within a Bayesian framework: a data-augmented independence MH-sampler, an auxiliary mixture sampler and a hybrid auxiliary mixture (HAM) sampler. All sampling procedures are based on algorithms using data augmentation, where the regression coefficients are estimated by rewriting the logit model as a latent variable model called difference random utility model (dRUM).

Package details

AuthorAgnes Fussl
Date of publication2014-03-12 18:11:36
MaintainerAgnes Fussl <[email protected]>
Package repositoryView on CRAN
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binomlogit documentation built on May 29, 2017, 9:43 a.m.