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cff-version: 1.2.0
message: 'To cite package "sparseSEM" in publications use:'
type: software
license: GPL-1.0-only
title: 'sparseSEM: Elastic Net Penalized Maximum Likelihood for Structural Equation
  Models with Network GPT Framework'
version: '4.1'
doi: 10.32614/CRAN.package.sparseSEM
abstract: '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.'
authors:
- family-names: Huang
  given-names: Anhui
  email: anhuihuang@gmail.com
repository: https://CRAN.R-project.org/package=sparseSEM
date-released: '2024-10-25'
contact:
- family-names: Huang
  given-names: Anhui
  email: anhuihuang@gmail.com