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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.

Versions across snapshots

VersionRepositoryFileSize
1.5.0 rolling linux/jammy R-4.5 LAWBL_1.5.0.tar.gz 611.9 KiB
1.5.0 rolling linux/noble R-4.5 LAWBL_1.5.0.tar.gz 611.9 KiB
1.5.0 rolling source/ R- LAWBL_1.5.0.tar.gz 481.9 KiB
1.5.0 latest linux/jammy R-4.5 LAWBL_1.5.0.tar.gz 611.9 KiB
1.5.0 latest linux/noble R-4.5 LAWBL_1.5.0.tar.gz 611.9 KiB
1.5.0 latest source/ R- LAWBL_1.5.0.tar.gz 481.9 KiB
1.5.0 2026-04-26 source/ R- LAWBL_1.5.0.tar.gz 481.9 KiB
1.5.0 2026-04-23 source/ R- LAWBL_1.5.0.tar.gz 481.9 KiB
1.5.0 2026-04-09 windows/windows R-4.5 LAWBL_1.5.0.zip 615.4 KiB
1.5.0 2025-04-20 source/ R- LAWBL_1.5.0.tar.gz 481.9 KiB

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