Package: pcaPP 2.0-4-1

pcaPP: Robust PCA by Projection Pursuit

Provides functions for robust PCA by projection pursuit. The methods are described in Croux et al. (2006) <doi:10.2139/ssrn.968376>, Croux et al. (2013) <doi:10.1080/00401706.2012.727746>, Todorov and Filzmoser (2013) <doi:10.1007/978-3-642-33042-1_31>.

Authors:Peter Filzmoser [aut], Heinrich Fritz [aut], Klaudius Kalcher [aut], Valentin Todorov [cre]

pcaPP_2.0-4-1.tar.gz
pcaPP_2.0-4-1.zip(r-4.5)pcaPP_2.0-4-1.zip(r-4.4)pcaPP_2.0-4-1.zip(r-4.3)
pcaPP_2.0-4-1.tgz(r-4.4-x86_64)pcaPP_2.0-4-1.tgz(r-4.4-arm64)pcaPP_2.0-4-1.tgz(r-4.3-x86_64)pcaPP_2.0-4-1.tgz(r-4.3-arm64)
pcaPP_2.0-4-1.tar.gz(r-4.5-noble)pcaPP_2.0-4-1.tar.gz(r-4.4-noble)
pcaPP_2.0-4-1.tgz(r-4.4-emscripten)pcaPP_2.0-4-1.tgz(r-4.3-emscripten)
pcaPP.pdf |pcaPP.html
pcaPP/json (API)

# Install 'pcaPP' in R:
install.packages('pcaPP', repos = c('https://valentint.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/valentint/pcapp/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

22 exports 1 stars 10.92 score 1 dependencies 335 dependents 8 mentions 191 scripts 36.2k downloads

Last updated 2 months agofrom:8d312e74f8. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 16 2024
R-4.5-win-x86_64OKSep 16 2024
R-4.5-linux-x86_64OKSep 16 2024
R-4.4-win-x86_64OKSep 16 2024
R-4.4-mac-x86_64OKSep 16 2024
R-4.4-mac-aarch64OKSep 16 2024
R-4.3-win-x86_64OKSep 16 2024
R-4.3-mac-x86_64OKSep 16 2024
R-4.3-mac-aarch64OKSep 16 2024

Exports:cor.fkcovPCcovPCAgridcovPCAprojdata.Zoul1medianl1median_BFGSl1median_CGl1median_HoCrl1median_NLMl1median_NMl1median_VaZhobjplotopt.BICopt.TPOPCAgridPCAprojPCdiagplotplotcovqnScaleAdvsPCAgrid

Dependencies:mvtnorm

Compiling pcaPP for Matlab

Rendered frommatlab.rnwusingutils::Sweaveon Sep 16 2024.

Last update: 2022-07-08
Started: 2022-07-08