plsmmLasso
Variable Selection and Inference for Partial Semiparametric Linear Mixed-Effects Model
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.1.0 |
rolling linux/jammy R-4.5 | plsmmLasso_1.1.0.tar.gz |
697.2 KiB |
1.1.0 |
rolling linux/noble R-4.5 | plsmmLasso_1.1.0.tar.gz |
697.2 KiB |
1.1.0 |
rolling source/ R- | plsmmLasso_1.1.0.tar.gz |
640.9 KiB |
1.1.0 |
latest linux/jammy R-4.5 | plsmmLasso_1.1.0.tar.gz |
697.2 KiB |
1.1.0 |
latest linux/noble R-4.5 | plsmmLasso_1.1.0.tar.gz |
697.2 KiB |
1.1.0 |
latest source/ R- | plsmmLasso_1.1.0.tar.gz |
640.9 KiB |
1.1.0 |
2026-04-26 source/ R- | plsmmLasso_1.1.0.tar.gz |
640.9 KiB |
1.1.0 |
2026-04-23 source/ R- | plsmmLasso_1.1.0.tar.gz |
640.9 KiB |
1.1.0 |
2026-04-09 windows/windows R-4.5 | plsmmLasso_1.1.0.zip |
703.6 KiB |
1.1.0 |
2025-04-20 source/ R- | plsmmLasso_1.1.0.tar.gz |
640.9 KiB |