| 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.dpGLM_data | |
| print.hdpGLM | |
| print.hdpGLM_data | |
| 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 |