DESCRIPTION

Package: cauchypca
Type: Package
Title: Robust Principal Component Analysis Using the Cauchy
        Distribution
Version: 1.3
Date: 2024-01-24
Authors@R: c( person("Michail", "Tsagris", role = c("aut", "cre"), email = "mtsagris@uoc.gr"), 
              person("Aisha", "Fayomi", role = c("ctb"), email = "afayomi@kau.edu.sa"),
              person("Yannis", "Pantazis", role = c("ctb"), email = "pantazis@iacm.forth.gr"),
              person("Andrew T.A.", "Wood", role = c("ctb"), email = "Andrew.Wood@anu.edu.au") )
Author: Michail Tsagris [aut, cre],
  Aisha Fayomi [ctb],
  Yannis Pantazis [ctb],
  Andrew T.A. Wood [ctb]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: doParallel, foreach, parallel, Rfast, Rfast2, stats
Description: 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>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2024-01-24 15:34:52 UTC; mtsag
Repository: CRAN
Date/Publication: 2024-01-24 19:50:02 UTC