Package: sparseSEM
Type: Package
Title: Elastic Net Penalized Maximum Likelihood for Structural Equation
        Models with Network GPT Framework
Version: 4.1
Date: 2024-10-25
Authors@R: c(person("Anhui", "Huang", role=c("aut","ctb", "cre" ), email="anhuihuang@gmail.com"))
Maintainer: Anhui Huang <anhuihuang@gmail.com>
Description: Provides elastic net penalized maximum likelihood
        estimator for structural equation models (SEM). The package
        implements `lasso` and `elastic net` (l1/l2) penalized SEM and
        estimates the model parameters with an efficient block
        coordinate ascent algorithm that maximizes the penalized
        likelihood of the SEM.  Hyperparameters are inferred from
        cross-validation (CV).  A Stability Selection (STS) function is
        also available to provide accurate causal effect selection. The
        software achieves high accuracy performance through a `Network
        Generative Pre-trained Transformer` (Network GPT) Framework
        with two steps: 1) pre-trains the model to generate a complete
        (fully connected) graph; and 2) uses the complete graph as the
        initial state to fit the `elastic net` penalized SEM.
Depends: R (>= 3.5.0)
Imports: parallel
License: GPL
Packaged: 2026-07-03 13:08:19 UTC; root
NeedsCompilation: yes
Suggests: knitr,plot.matrix
VignetteBuilder: knitr
Author: Anhui Huang [aut, ctb, cre]
Repository: https://cran.r-universe.dev
Date/Publication: 2024-10-27 15:30:02 UTC
RemoteUrl: https://github.com/cran/sparseSEM
RemoteRef: HEAD
RemoteSha: d46e74d47a7fc4c801b0016e95ed45db8c808bc3