Package: rsvddpd
Type: Package
Encoding: UTF-8
Title: Robust Singular Value Decomposition using Density Power
        Divergence
Version: 1.0.0
Date: 2021-10-23
Authors@R: person("Subhrajyoty", "Roy", email = "subhrajyotyroy@gmail.com", role = c("aut", "cre"))
Description: Computing singular value decomposition with robustness is a challenging task. 
    This package provides an implementation of computing robust SVD using density power 
    divergence (<arXiv:2109.10680>). It combines the idea of robustness and efficiency in estimation
    based on a tuning parameter. It also provides utility functions to simulate various
    scenarios to compare performances of different algorithms.
License: MIT + file LICENSE
Imports: Rcpp (>= 1.0.5), MASS, stats, utils, matrixStats
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, microbenchmark, pcaMethods
VignetteBuilder: knitr
URL: https://github.com/subroy13/rsvddpd
BugReports: https://github.com/subroy13/rsvddpd/issues
NeedsCompilation: yes
Packaged: 2021-10-27 10:45:18 UTC; subroy13
Author: Subhrajyoty Roy [aut, cre]
Maintainer: Subhrajyoty Roy <subhrajyotyroy@gmail.com>
Repository: CRAN
Date/Publication: 2021-10-27 14:30:02 UTC
Built: R 4.1.0; x86_64-apple-darwin17.0; 2021-10-28 11:57:35 UTC; unix
Archs: rsvddpd.so.dSYM
