Penalized Linear Mixed Models for Correlated Data

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Documentation for package ‘plmmr’ version 4.1.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

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 non-convex 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