The FPCdpca Criterion on Distributed Principal Component Analysis R package FPCdpca version 0.4.0 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. (2025) <doi:10.1016/j.physa.2024.130308>. Software Depends: R (>= 3.5.0) Imports: matrixcalc,rsvd,stats Suggests: testthat (>= 3.0.0) Guangbao Guo <ggb11111111@163.com> Comprehensive R Archive Network (CRAN) Guangbao Guo [aut, cre] (ORCID: <https://orcid.org/0000-0002-4115-6218>), Jiarui Li [aut] Apache License (== 2.0) 2026-01-21 application/tgz https://CRAN.R-project.org/package=FPCdpca doi:10.32614/CRAN.package.FPCdpca