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 <>
Package repositoryView on CRAN
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LAWBL documentation built on April 2, 2021, 1:05 a.m.