R: High Dimensional Penalized Generalized Linear Mixed Models (pGLMM)

# High Dimensional Penalized Generalized Linear Mixed Models (pGLMM)

## Documentation for package ‘glmmPen’ version 1.5.4.8

- DESCRIPTION file
- Package README

## Help Pages

adaptControl | Control of Metropolis-within-Gibbs Adaptive Random Walk Sampling Procedure Controls the adaptive random walk Metropolis-within-Gibbs sampling procedure.
basal | Basal dataset: A composition of cancer datasets with top scoring pairs (TSPs) as covariates and binary response indicating if the subject's cancer subtype was basal-like. A dataset composed of four datasets combined from studies that contain gene expression data from subjects with several types of cancer. Two of these datasets contain gene expression data for subjects with Pancreatic Ductal Adenocarcinoma (PDAC), one dataset contains data for subjects with Breast Cancer, and the fourth dataset contains data for subjects with Bladder Cancer. The response of interest is whether or not the subject's cancer subtype was the basal-like subtype. See articles Rashid et al. (2020) "Modeling Between-Study Heterogeneity for Improved Replicability in Gene Signature Selection and Clinical Prediction" and Moffitt et al. (2015) "Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma" for further details on these four datasets.
BIC.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
coef.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
coef.pglmmObj, | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
family.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
fitted.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
fitted.pglmmObj, | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
fixef.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
fixef.pglmmObj, | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
formula.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
formula.pglmmObj, | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
glmm | Fit a Generalized Mixed Model via Monte Carlo Expectation Conditional Minimization (MCECM)
glmmPen | Fit Penalized Generalized Mixed Models via Monte Carlo Expectation Conditional Minimization (MCECM)
glmmPen_FA | Fit Penalized Generalized Mixed Models via Monte Carlo Expectation Conditional Minimization (MCECM)
glmm_FA | Fit a Generalized Mixed Model via Monte Carlo Expectation Conditional Minimization (MCECM)
lambdaControl | Control of Penalization Parameters and Selection Criteria
LambdaSeq | Calculation of Penalty Parameter Sequence (Lambda Sequence)
logLik.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
logLik.pglmmObj, | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
model.frame.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
model.frame.pglmmObj, | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
model.matrix.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
model.matrix.pglmmObj, | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
ngrps.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
nobs.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
optimControl | Control of Penalized Generalized Linear Mixed Model Fitting
pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
pglmmObj-class | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
pglmmObj-method, | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
phmm | Fit a Proportional Hazards Mixed Model via Monte Carlo Expectation Conditional Minimization (MCECM) using a Piecewise Constant Hazard Mixed Model Approximation
phmmPen | Fit Penalized Proportional Hazards Mixed Models via Monte Carlo Expectation Conditional Minimization (MCECM) using a Piecewise Constant Hazard Mixed Model Approximation
phmmPen_FA | Fit a Penalized Proportional Hazards Mixed Model via Monte Carlo Expectation Conditional Minimization (MCECM) using a Piecewise Constant Hazard Mixed Model Approximation
phmm_FA | Fit a Proportional Hazards Mixed Model via Monte Carlo Expectation Conditional Minimization (MCECM) using a Piecewise Constant Hazard Mixed Model Approximation
plot.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
plot.pglmmObj, | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
plot_mcmc | Plot Diagnostics for MCMC Posterior Draws of the Random Effects
predict.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
predict.pglmmObj, | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
print.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
print.pglmmObj, | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
ranef.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
ranef.pglmmObj, | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
rControl | Control of Latent Factor Model Number Estimation Constructs the control structure for the estimation of the number of latent factors (r) for use within the 'glmmPen_FA' and 'glmm_FA' estimation procedures.
residuals.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
residuals.pglmmObj, | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
selectControl | Control of Penalization Parameters and Selection Criteria
show, | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
sigma.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
sigma.pglmmObj, | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
sim.data | Simulates data to use for the 'glmmPen' package
sim.data.FA | Simulates data to use for the 'glmmPen' package
sim.data.piecewise.exp | Simulates data to use for the 'glmmPen' package
sim.data.weibull | Simulates data to use for the 'glmmPen' package
summary.pglmmObj | Class 'pglmmObj' of Fitted Penalized Generalized Mixed-Effects Models for package 'glmmPen'
survivalControl | Control for Fitting Piecewise Constant Hazard Mixed Models as an Approximation to Fitting Cox Proportional Hazards Mixed Models
survival_data | Convert Input Survival Data Into Long-Form Data Needed for Fitting a Piecewise Exponential Model