An analytical framework for latent variables with different Bayesian learning methods, currently based on the partially confirmatory factor analysis (PCFA) model by Chen, Guo, Zhang, & Pan (2020) <doi:10.1037/met0000293>.
| Version: | 1.1.0 |
| Depends: | R (≥ 3.6.0) |
| Imports: | stats, MASS, coda |
| Suggests: | knitr, rmarkdown, testthat |
| Published: | 2020-07-23 |
| Author: | Jinsong Chen [aut, cre, cph] |
| Maintainer: | Jinsong Chen <jinsong.chen at live.com> |
| BugReports: | https://github.com/Jinsong-Chen/LAWBL/issues |
| License: | GPL-3 |
| URL: | https://github.com/Jinsong-Chen/LAWBL, https://jinsong-chen.github.io/LAWBL |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | LAWBL results |
| Reference manual: | LAWBL.pdf |
| Vignettes: |
pcfa-examples |
| Package source: | LAWBL_1.1.0.tar.gz |
| Windows binaries: | r-devel: LAWBL_1.1.0.zip, r-release: LAWBL_1.1.0.zip, r-oldrel: LAWBL_1.1.0.zip |
| macOS binaries: | r-release: LAWBL_1.1.0.tgz, r-oldrel: LAWBL_1.1.0.tgz |
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