Mixture Models for Binomial and Longitudinal Data


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Documentation for package ‘binomialMix’ version 1.0.1

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adcampaign Advertising campaign dataset
extract_id Extract levels as numeric from id column of the dataset
extract_target Extract target value of GLM
extract_variables Extract variables from GLM model
Incomplete_Loglikelihood_binomiale Calculate the incomplete loglikelihood from mixture of binomial
init_design_matrices Initialize design matrices from dataframe to cluster
init_lambda Initialize the vector lambda of mixture proportion
init_subset Initialize the estimation of beta
init_tau Initialize the matrix probability of each levels id to be in the clusters
log_density_binom Calculate de log density of a binomial
my_BIC Calculate the Bayesian Information Criterion (BIC)
my_ICL Calculate the Integrated Complete Likelihood (ICL)
runEM Run an EM algorithm to obtain a mixture of binomial with K clusters
update_beta M-step : update of beta parameters
update_tau E-step : update of tau
update_w M-step : Update the diagonal matrix W from beta iterative equation
update_z M-step : Update the matrix of working variables Z from beta iterative equation