LAWBL: Latent (Variable) Analysis with Bayesian Learning

A variety of models to analyze latent variables based on Bayesian learning: the partially CFA (Chen, Guo, Zhang, & Pan, 2020) <DOI: 10.1037/met0000293>; generalized PCFA; partially confirmatory IRM (Chen, 2020) <DOI: 10.1007/s11336-020-09724-3>; Bayesian regularized EFA <DOI: 10.1080/10705511.2020.1854763>; Fully and partially EFA.

Package details

AuthorJinsong Chen [aut, cre, cph]
MaintainerJinsong Chen <jinsong.chen@live.com>
LicenseGPL-3
Version1.4.0
URL https://github.com/Jinsong-Chen/LAWBL https://jinsong-chen.github.io/LAWBL/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("LAWBL")

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LAWBL documentation built on April 2, 2021, 1:05 a.m.