Penalized Linear Mixed Models for Correlated Data
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Documentation for package ‘plmmr’ version 4.3.0
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. |
| 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.cv_plmm | Predict method for 'cv_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 a filebacked 'big.matrix' |
| 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 'plmm' objects |
| unzip_example_data | Companion function to unzip the '.gz' files that ship with the 'plmmr' package. |