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.
Michail Tsagris mtsagris@uoc.gr, Aisha Fayomi afayomi@kau.edu.sa, Yannis Pantazis pantazis@iacm.forth.gr and Andrew T.A. Wood Andrew.Wood@anu.edu.au.
Michail Tsagris <mtsagris@uoc.gr>.
| Package: | cauchypca |
| Type: | Package |
| Version: | 1.3 |
| Date: | 2024-01-24 |
| License: | GPL-2 |
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. https://doi.org/10.1007/s11222-023-10328-x