Implements a generalized version of principal components analysis (GLM-PCA) for dimension reduction of non-normally distributed data such as counts or binary matrices. Townes FW, Hicks SC, Aryee MJ, Irizarry RA (2019) <doi:10.1101/574574>. Townes FW (2019) <arXiv:1907.02647>.
| Version: | 0.1.0 |
| Depends: | R (≥ 3.6), stats |
| Suggests: | knitr, MASS, testthat, covr, ggplot2 |
| Published: | 2019-09-27 |
| Author: | F. William Townes [aut, cre, cph], Kelly Street [aut], Jake Yeung [ctb] |
| Maintainer: | F. William Townes <will.townes at gmail.com> |
| BugReports: | https://github.com/willtownes/glmpca/issues |
| License: | Artistic-2.0 |
| URL: | https://github.com/willtownes/glmpca |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | glmpca results |
| Reference manual: | glmpca.pdf |
| Vignettes: |
Title of your vignette |
| Package source: | glmpca_0.1.0.tar.gz |
| Windows binaries: | r-devel: glmpca_0.1.0.zip, r-devel-gcc8: glmpca_0.1.0.zip, r-release: glmpca_0.1.0.zip, r-oldrel: not available |
| OS X binaries: | r-release: glmpca_0.1.0.tgz, r-oldrel: not available |
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