Bayesian Profile Regression using Generalised Linear Mixed
Models
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Documentation for package ‘ProfileGLMM’ version 1.1.0
Help Pages
| encodeCat | One-Hot Encodes Factor Variables (FIRST Level as Reference) |
| examp | List of the different outputs of the main functions for the examples |
| exposure_data | Simulated Data and Parameters for a exposure profile linear mixed model |
| piecewise_data | Simulated Data and Parameters for a Piecewise Example |
| plot.pglmm_fit | Plot method for pglmm_fit continuous covariates cluster characteristics |
| predict.pglmm_fit | Prediction of cluster memberships and outcomes |
| print.pglmm_data | Print method for pglmm_data |
| print.pglmm_fit | Print method for pglmm_fit |
| print.pglmm_mcmc | Print method for pglmm_mcmc |
| prior_init | Initialize the prior hyperparameters for the Profile GLMM |
| profileGLMM_Gibbs | R Wrapper for Profile GLMM Gibbs Sampler (C++ backend) |
| profileGLMM_postProcess | Post-process MCMC Output for Profile GLMM |
| profileGLMM_preprocess | Preprocess the data from a list describing the profile LMM model |
| summary.pglmm_fit | Print method for pglmm_fit |
| theta_init | Initialize the variables for the Gibbs sampler chain |