Efficient MCMC for Binomial Logit Models

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).


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install.packages("binomlogit")

1.2 by Agnes Fussl, 5 years ago


Browse source code at https://github.com/cran/binomlogit


Authors: Agnes Fussl


Documentation:   PDF Manual  


GPL-3 license



See at CRAN