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cauchypca

Robust Principal Component Analysis Using the Cauchy Distribution

v1.3 · Jan 24, 2024 · GPL (>= 2)

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>.

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r-devel-linux-x86_64-debian-clang ERROR
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
r-oldrel-macos-x86_64 OK
r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
r-release-linux-x86_64 OK
r-release-macos-arm64 OK
r-release-macos-x86_64 OK
r-release-windows-x86_64 OK
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ERROR r-devel-linux-x86_64-debian-clang

package dependencies

Package required but not available: ‘Rfast2’

See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.
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Check History

ERROR 13 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Mar 9, 2026
ERROR r-devel-linux-x86_64-debian-clang

package dependencies

Package required but not available: ‘Rfast2’

See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.

Dependency Network

Dependencies Reverse dependencies doParallel foreach Rfast Rfast2 cauchypca

Version History

new 1.3 Mar 9, 2026