Robust Singular Value Decomposition using Density Power Divergence

Computing singular value decomposition with robustness is a challenging task. This package provides an implementation of computing robust SVD using density power divergence (). 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.


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install.packages("rsvddpd")

1.0.0 by Subhrajyoty Roy, a month ago


https://github.com/subroy13/rsvddpd


Report a bug at https://github.com/subroy13/rsvddpd/issues


Browse source code at https://github.com/cran/rsvddpd


Authors: Subhrajyoty Roy [aut, cre]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports Rcpp, MASS, stats, utils, matrixStats

Suggests knitr, rmarkdown, microbenchmark, pcaMethods

Linking to Rcpp, RcppArmadillo


See at CRAN