Robust Singular Value Decomposition using Density Power Divergence R package rsvddpd version 1.0.1 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. Software Imports: Rcpp (>= 1.0.5), MASS, stats, utils, matrixStats LinkingTo: Rcpp, RcppArmadillo Suggests: knitr, rmarkdown, microbenchmark, pcaMethods, V8 Subhrajyoty Roy <subhrajyotyroy@gmail.com> Comprehensive R Archive Network (CRAN) Subhrajyoty Roy [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=rsvddpd/LICENSE) 2025-09-20 application/tgz https://CRAN.R-project.org/package=rsvddpd doi:10.32614/CRAN.package.rsvddpd