Implements a partial linear semiparametric mixed-effects model (PLSMM) featuring a random intercept and applies a lasso penalty to both the fixed effects and the coefficients associated with the nonlinear function. The model also accommodates interactions between the nonlinear function and a grouping variable, allowing for the capture of group-specific nonlinearities. Nonlinear functions are modeled using a set of bases functions. Estimation is conducted using a penalized Expectation-Maximization algorithm, and the package offers flexibility in choosing between various information criteria for model selection. Post-selection inference is carried out using a debiasing method, while inference on the nonlinear functions employs a bootstrap approach.
Version: | 1.1.0 |
Imports: | dplyr, ggplot2, glmnet, hdi, MASS, mvtnorm, rlang, scalreg, stats |
Published: | 2024-06-04 |
Author: | Sami Leon [aut, cre, cph], Tong Tong Wu [ths] |
Maintainer: | Sami Leon <samileon at hotmail.fr> |
BugReports: | https://github.com/Sami-Leon/plsmmLasso/issues |
License: | GPL (≥ 3) |
URL: | https://github.com/Sami-Leon/plsmmLasso |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | plsmmLasso results |
Package source: | plsmmLasso_1.1.0.tar.gz |
Windows binaries: | r-devel: plsmmLasso_1.1.0.zip, r-release: plsmmLasso_1.1.0.zip, r-oldrel: plsmmLasso_1.1.0.zip |
macOS binaries: | r-release (arm64): plsmmLasso_1.1.0.tgz, r-oldrel (arm64): plsmmLasso_1.1.0.tgz, r-release (x86_64): plsmmLasso_1.1.0.tgz, r-oldrel (x86_64): plsmmLasso_1.1.0.tgz |
Old sources: | plsmmLasso archive |
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