# Penalized Linear Mixed Models for Correlated Data

## Documentation for package ‘plmmr’ version 4.2.3

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

admix | Admix: Semi-simulated SNP data
coef.cv_plmm | Coef method for "cv_plmm" class
coef.plmm | Coef method for "plmm" class
create_design | a function to create a design for PLMM modeling
cv_plmm | Cross-validation for plmm
find_example_data | A function to help with accessing example PLINK files
lasso | helper function to implement lasso penalty
plmm | Fit a linear mixed model via penalized maximum likelihood.
plmm_loss | Loss method for "plmm" class
plot.cv_plmm | Plot method for cv_plmm class
plot.plmm | Plot method for plmm class
predict.plmm | Predict method for plmm class
print.summary.cv_plmm | Print method for summary.cv_plmm objects
print.summary.plmm | A function to print the summary of a 'plmm' model
process_delim | A function to read in large data files as an FBM
process_plink | Preprocess PLINK files using the 'bigsnpr' package
relatedness_mat | Calculate a relatedness matrix
summary.cv_plmm | A summary function for cv_plmm objects
summary.plmm | A summary method for the plmm objects
unzip_example_data | For Linux/Unix and MacOS only, here is a companion function to unzip the .gz files that ship with the 'plmmr' package