binomlogit: 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).
Version: |
1.2 |
Published: |
2014-03-12 |
Author: |
Agnes Fussl |
Maintainer: |
Agnes Fussl <avf at gmx.at> |
License: |
GPL-3 |
NeedsCompilation: |
no |
CRAN checks: |
binomlogit results |
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