R implementation of Maximum Likelihood Principal Component Analysis The main idea of this package is to have an alternative way of PCA for subspace modeling that considers measurement errors. More details can be found in Peter D. Wentzell (2009) <doi:10.1016/B978-0-444-64165-6.03029-9>.
| Version: | 0.0.1 |
| Depends: | R (≥ 2.10) |
| Imports: | base, Matrix, pracma, RSpectra |
| Suggests: | testthat, knitr, rmarkdown |
| Published: | 2020-11-05 |
| DOI: | 10.32614/CRAN.package.RMLPCA |
| Author: | Renan Santos Barbosa [aut, cre] |
| Maintainer: | Renan Santos Barbosa <renansantosbarbosa at usp.br> |
| BugReports: | https://github.com/renanestatcamp/RMLPCA/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/renanestatcamp/RMLPCA |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | RMLPCA results |
| Reference manual: | RMLPCA.pdf |
| Package source: | RMLPCA_0.0.1.tar.gz |
| Windows binaries: | r-devel: RMLPCA_0.0.1.zip, r-release: RMLPCA_0.0.1.zip, r-oldrel: RMLPCA_0.0.1.zip |
| macOS binaries: | r-release (arm64): RMLPCA_0.0.1.tgz, r-oldrel (arm64): RMLPCA_0.0.1.tgz, r-release (x86_64): RMLPCA_0.0.1.tgz, r-oldrel (x86_64): RMLPCA_0.0.1.tgz |
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