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FPCdpca  

The FPCdpca Criterion on Distributed Principal Component Analysis
View on CRAN: Click here


Download and install FPCdpca package within the R console
Install from CRAN:
install.packages("FPCdpca")

Install from Github:
library("remotes")
install_github("cran/FPCdpca")

Install by package version:
library("remotes")
install_version("FPCdpca", "0.4.0")



Attach the package and use:
library("FPCdpca")
Maintained by
Guangbao Guo
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-05-27
Latest Update: 2025-05-09
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) <doi:10.1007/s00180-020-00974-4>.
How to cite:
Guangbao Guo (2024). FPCdpca: The FPCdpca Criterion on Distributed Principal Component Analysis. R package version 0.4.0, https://cran.r-project.org/web/packages/FPCdpca. Accessed 27 Jun. 2026.
Previous versions and publish date:
0.1.0 (2024-05-27 19:30), 0.2.0 (2025-04-10 05:20), 0.3.0 (2025-05-09 04:50)
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Complete documentation for FPCdpca
Functions, R codes and Examples using the FPCdpca R package
Full FPCdpca package functions and examples
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