ltsspca: Sparse Principal Component Based on Least Trimmed Squares

Implementation of robust and sparse PCA algorithm of Wang and Van Aelst (2019) <doi:10.1080/00401706.2019.1671234>.

Version: 0.1.0
Depends: R (≥ 3.2.0)
Imports: Rcpp (≥ 1.0.1), pracma
LinkingTo: Rcpp, RcppArmadillo
Suggests: robustbase, rrcov, stats, mvtnorm, graphics, knitr, rmarkdown, testthat
Published: 2019-10-09
Author: Yixin Wang [aut, cre], Stefan Van Aelst [aut], Holger Cevallos Valdiviezo [ctb] (Original R code for the LTS-PCA algorithm), Tom Reynkens [ctb] (Original R code for angle in the rospca package)
Maintainer: Yixin Wang <wangyixin07 at outlook.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README
CRAN checks: ltsspca results

Downloads:

Reference manual: ltsspca.pdf
Vignettes: LTS-SPCA example
Package source: ltsspca_0.1.0.tar.gz
Windows binaries: r-devel: ltsspca_0.1.0.zip, r-release: ltsspca_0.1.0.zip, r-oldrel: ltsspca_0.1.0.zip
OS X binaries: r-release: ltsspca_0.1.0.tgz, r-oldrel: ltsspca_0.1.0.tgz

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