R: Clustering Multinomial Count Data under the Presence of Covariates

# Clustering Multinomial Count Data under the Presence of Covariates

## Documentation for package ‘multinomialLogitMix’ version 1.1

- DESCRIPTION file

## Help Pages

multinomialLogitMix-package | Clustering Multinomial Count Data under the Presence of Covariates
dealWithLabelSwitching | Post-process the generated MCMC sample in order to undo possible label switching.
expected_complete_LL | Expected complete LL
gibbs_mala_sampler | The core of the Hybrid Gibbs/MALA MCMC sampler for the multinomial logit mixture.
gibbs_mala_sampler_ppt | Prior parallel tempering scheme of hybrid Gibbs/MALA MCMC samplers for the multinomial logit mixture.
log_dirichlet_pdf | Log-density function of the Dirichlet distribution
log_mix_prior_derivative | Proposal mechanism of the MALA step.
log_prior_mix | Proposal mechanism of the MALA step.
mala_proposal | Proposal mechanism of the MALA step.
mala_proposal_cpp | Proposal mechanism of the MALA step.
mixLoglikelihood_GLM | Log-likelihood of the multinomial logit.
mix_mnm_logistic | EM algorithm
multinomialLogitMix | Main function
multinomial_logistic_EM | Part of the EM algorithm for multinomial logit mixture
myDirichlet | Simulate from the Dirichlet distribution
newton_raphson_mstep | M-step of the EM algorithm
shakeEM_GLM | Shake-small EM
simulate_multinomial_data | Synthetic data generator
splitEM_GLM | Split-small EM scheme.