Package: glmpca
Title: Dimension Reduction of Non-Normally Distributed Data
Version: 0.2.0
Description: 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:10.1186/s13059-019-1861-6>.
    Townes FW (2019) <arXiv:1907.02647>.
Authors@R: c(person("F. William", "Townes", email = "will.townes@gmail.com",
            role = c("aut", "cre", "cph")),
            person("Kelly", "Street", email = "street.kelly@gmail.com", role="aut"),
            person("Jake", "Yeung", email = "jakeyeung@gmail.com", role="ctb"))
License: LGPL (>= 3) | file LICENSE
Depends: R (>= 3.5),
Imports: MASS, methods, stats, utils
Suggests: covr, ggplot2, knitr, logisticPCA, markdown, Matrix,
        testthat,
URL: https://github.com/willtownes/glmpca
BugReports: https://github.com/willtownes/glmpca/issues
Language: en-US
VignetteBuilder: knitr
LazyData: false
RoxygenNote: 7.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-07-18 17:07:28 UTC; townesf
Author: F. William Townes [aut, cre, cph],
  Kelly Street [aut],
  Jake Yeung [ctb]
Maintainer: F. William Townes <will.townes@gmail.com>
Repository: CRAN
Date/Publication: 2020-07-18 17:30:02 UTC
Built: R 4.6.0; ; 2026-04-26 19:12:36 UTC; unix
