Function reference • hdpGLM

All functions
`classify()`	Classify data points
`coef(<dpGLM>)`	Extract dpGLM fitted coefficients
`coef(<hdpGLM>)`	Extract hdpGLM fitted coefficients
`hdpGLM()`	Fit Hierarchical Dirichlet Process GLM
`hdpGLM_classify()`	Deprecated
`hdpGLM_package`	hdpGLM: A package for computating Hierarchical Dirichlet Process Generalized Linear Models
`hdpGLM_simParameters()`	Simulate the parameters of the model
`hdpGLM_simulateData()`	Simulate a Data Set from hdpGLM
`mcmc_info.dpGLM()`	mcmc
`mcmc_info.hdpGLM()`	mcmc
`nclusters()`	nclusters
`plot(<dpGLM>)`	Default plot for class dpGLM
`plot(<hdpGLM>)`	Plot
`plot_beta()`	Plot beta posterior distribution
`plot_beta_sim()`	Plot simulated data
`plot_hdpglm()`	Plot posterior distributions
`plot_pexp_beta()`	Plot beta posterior expectation
`plot_tau()`	Plot tau
`predict(<dpGLM>)`	dpGLM Predicted values
`predict(<hdpGLM>)`	hdpGLM Predicted values
`print(<dpGLM>)`	Print
`print(<dpGLM_data>)`	Print
`print(<hdpGLM>)`	Print
`print(<hdpGLM_data>)`	Print
`summary(<dpGLM>)`	Summary for dpGLM class
`summary(<dpGLM_data>)`	Summary dpGLM data
`summary(<hdpGLM>)`	Summary for hdpGLM class
`summary(<hdpGLM_data>)`	Summary
`summary_tidy()`	Tidy summary
`welfare`	Fake data set with 2000 observations
`welfare2`	Fake data set with 2000 observations

Reference