Package: plsmmLasso
Title: Variable Selection and Inference for Partial Semiparametric
        Linear Mixed-Effects Model
Version: 1.1.0
Authors@R: c(
  person(given = "Sami",
    family = "Leon",
    email = "samileon@hotmail.fr",
    role = c("aut", "cre", "cph"),
    comment = c(ORCID = "0000-0001-9138-9450")),
  person(given = "Tong Tong",
    family = "Wu",
    role = c("ths"),
    comment = c(ORCID = "0000-0002-1175-9923"))
  )
Description: 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.
License: GPL (>= 3)
Imports: dplyr, ggplot2, glmnet, hdi, MASS, mvtnorm, rlang, scalreg,
        stats
Encoding: UTF-8
RoxygenNote: 7.3.1
URL: https://github.com/Sami-Leon/plsmmLasso
BugReports: https://github.com/Sami-Leon/plsmmLasso/issues
NeedsCompilation: no
Packaged: 2024-06-03 15:21:00 UTC; sami
Author: Sami Leon [aut, cre, cph] (<https://orcid.org/0000-0001-9138-9450>),
  Tong Tong Wu [ths] (<https://orcid.org/0000-0002-1175-9923>)
Maintainer: Sami Leon <samileon@hotmail.fr>
Repository: CRAN
Date/Publication: 2024-06-04 09:45:47 UTC
Built: R 4.6.0; ; 2026-04-29 06:16:29 UTC; unix
