DESCRIPTION

Package: glmpca
Title: Dimension Reduction of Non-Normally Distributed Data
Version: 0.2.0.9000
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