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rsvddpd  

Robust Singular Value Decomposition using Density Power Divergence
View on CRAN: Click here


Download and install rsvddpd package within the R console
Install from CRAN:
install.packages("rsvddpd")

Install from Github:
library("remotes")
install_github("cran/rsvddpd")

Install by package version:
library("remotes")
install_version("rsvddpd", "1.0.0")



Attach the package and use:
library("rsvddpd")
Maintained by
Subhrajyoty Roy
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-10-27
Latest Update: 2021-10-27
Description:
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.
How to cite:
Subhrajyoty Roy (2021). rsvddpd: Robust Singular Value Decomposition using Density Power Divergence. R package version 1.0.0, https://cran.r-project.org/web/packages/rsvddpd. Accessed 06 Nov. 2024.
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Complete documentation for rsvddpd
Functions, R codes and Examples using the rsvddpd R package
Some associated functions: AddOutlier . cv.alpha . rSVDdpd . simSVD . 
Some associated R codes: RcppExports.R . rSVDdpd.R . simulation.R .  Full rsvddpd package functions and examples
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