CRAN/E | plsmmLasso

plsmmLasso

Variable Selection and Inference for Partial Semiparametric Linear Mixed-Effects Model

Installation

About

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.

github.com/Sami-Leon/plsmmLasso
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Key Metrics

Version 1.1.0
Published 2024-06-04 124 days ago
Needs compilation? no
License GPL (≥ 3)
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Maintainer

Maintainer

Sami Leon

Authors

Sami Leon

aut / cre / cph

Tong Tong Wu

ths

Material

README
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

plsmmLasso archive

Imports

dplyr
ggplot2
glmnet
hdi
MASS
mvtnorm
rlang
scalreg
stats