CRAN/E | cauchypca

cauchypca

Robust Principal Component Analysis Using the Cauchy Distribution

Installation

About

A new robust principal component analysis algorithm is implemented that relies upon the Cauchy Distribution. The algorithm is suitable for high dimensional data even if the sample size is less than the number of variables. The methodology is described in this paper: Fayomi A., Pantazis Y., Tsagris M. and Wood A.T.A. (2024). "Cauchy robust principal component analysis with applications to high-dimensional data sets". Statistics and Computing, 34: 26. doi:10.1007/s11222-023-10328-x.

Key Metrics

Version 1.3
R ≥ 4.0
Published 2024-01-24 97 days ago
Needs compilation? no
License GPL-2
License GPL-3
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Maintainer

Maintainer

Michail Tsagris

mtsagris@uoc.gr

Authors

Michail Tsagris

aut / cre

Aisha Fayomi

ctb

Yannis Pantazis

ctb

Andrew T.A. Wood

ctb

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

cauchypca archive

Depends

R ≥ 4.0

Imports

doParallel
foreach
parallel
Rfast
Rfast2
stats