Distributed Markov Chain Monte Carlo for Bayesian Inference in Marketing

Documentation for package ‘scalablebayesm’ version 0.2

combine_draws	Combine Lists of Draws From a Posterior Predictive Distribution
drawMixture	Gibbs Sampler Inference for a Mixture of Multivariate Normals
drawPosteriorParallel	Draw from Posterior Parallel Distribution
hello	A placeholder function using roxygen
partition_data	Partition Data Into Shards
rheteroLinearIndepMetrop	Distributed Independence Metropolis-Hastings Algorithm for Draws From Multivariate Normal Distribution
rheteroMnlIndepMetrop	Independence Metropolis-Hastings Algorithm for Draws From Multinomial Distribution
rhierLinearDPParallel	MCMC Algorithm for Hierarchical Linear Model with Dirichlet Process Prior Heterogeneity
rhierLinearMixtureParallel	MCMC Algorithm for Hierarchical Multinomial Linear Model with Mixture-of-Normals Heterogeneity
rhierMnlDPParallel	MCMC Algorithm for Hierarchical Multinomial Logit with Dirichlet Process Prior Heterogeneity
rhierMnlRwMixtureParallel	MCMC Algorithm for Hierarchical Multinomial Logit with Mixture-of-Normals Heterogeneity
sample_data	Sample Data
s_max	Calculate Maximum Number of Shards