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FPCdpca (version 0.1.0)

The FPCdpca Criterion on Distributed Principal Component Analysis

Description

We consider optimal subset selection in the setting that one needs to use only one data subset to represent the whole data set with minimum information loss, and devise a novel intersection-based criterion on selecting optimal subset, called as the FPC criterion, to handle with the optimal sub-estimator in distributed principal component analysis; That is, the FPCdpca. The philosophy of the package is described in Guo G. (2020) .

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Version

Install

install.packages('FPCdpca')

Monthly Downloads

449

Version

0.1.0

License

Apache License (== 2.0)

Maintainer

Guangbao Guo

Last Published

May 27th, 2024

Functions in FPCdpca (0.1.0)

FPC

FPC
Drsvd

Distributed random svd
Dsvd

Distributed svd
Drpca

Distributed random PCA
Drp

Distributed random projection
Dpca

Distributed PCA
Depca

Decentralized PCA