Computing singular value decomposition with robustness is a challenging task. This package provides an implementation of computing robust SVD using density power divergence (<doi:10.48550/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.
Version: 1.0.0 Imports: Rcpp (≥ 1.0.5), MASS, stats, utils, matrixStats LinkingTo: Rcpp, RcppArmadillo Suggests: knitr, rmarkdown, microbenchmark, pcaMethods Published: 2021-10-27 DOI: 10.32614/CRAN.package.rsvddpd Author: Subhrajyoty Roy [aut, cre] Maintainer: Subhrajyoty Roy <subhrajyotyroy at gmail.com> BugReports: https://github.com/subroy13/rsvddpd/issues License: MIT + file LICENSE URL: https://github.com/subroy13/rsvddpd NeedsCompilation: yes Materials: README, NEWS CRAN checks: rsvddpd results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=rsvddpd to link to this page.
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