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ltsspca  

Sparse Principal Component Based on Least Trimmed Squares
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("ltsspca", "0.1.0")



Attach the package and use:
library("ltsspca")
Maintained by
Yixin Wang
[Scholar Profile | Author Map]
First Published: 2019-10-09
Latest Update: 2019-10-09
Description:
Implementation of robust and sparse PCA algorithm of Wang and Van Aelst (2019) .
How to cite:
Yixin Wang (2019). ltsspca: Sparse Principal Component Based on Least Trimmed Squares. R package version 0.1.0, https://cran.r-project.org/web/packages/ltsspca. Accessed 29 Mar. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited ltsspca R package
View ltsspca citation profile
Other R packages that ltsspca depends, imports, suggests or enhances
Complete documentation for ltsspca
Functions, R codes and Examples using the ltsspca R package
Some associated functions: Angle . Glass . dataSim . ltspca . ltsspca . ltsspcaRw . mydiagPlot . sPCA_rSVD . 
Some associated R codes: Glass.R . RcppExports.R . angle.R . auxiliary_functions.R . dataSim.R . ltspca.R . ltsspca.R . mydiagplot.R . rwltsspca.R . spca_rsvd.R .  Full ltsspca package functions and examples
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