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sparseSEM  

Elastic Net Penalized Maximum Likelihood for Structural Equation Models with Network GPT Framework
View on CRAN: Click here


Download and install sparseSEM package within the R console
Install from CRAN:
install.packages("sparseSEM")

Install from Github:
library("remotes")
install_github("cran/sparseSEM")

Install by package version:
library("remotes")
install_version("sparseSEM", "4.1")



Attach the package and use:
library("sparseSEM")
Maintained by
Anhui Huang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-08-26
Latest Update: 2023-08-09
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.
How to cite:
Anhui Huang (2014). sparseSEM: Elastic Net Penalized Maximum Likelihood for Structural Equation Models with Network GPT Framework. R package version 4.1, https://cran.r-project.org/web/packages/sparseSEM. Accessed 21 Nov. 2024.
Previous versions and publish date:
2.3 (2014-08-26 15:41), 2.5 (2014-09-04 07:49), 3.8-1 (2023-05-04 13:10), 3.8-2 (2023-06-11 21:30), 3.8 (2023-04-21 14:40), 4.0 (2023-08-09 11:10)
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