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FPCdpca

The FPCdpca Criterion on Distributed Principal Component Analysis

v0.4.0 · Jan 20, 2026 · Apache License (== 2.0)

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. (2025) <doi:10.1016/j.physa.2024.130308>.

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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

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Dependencies Reverse dependencies matrixcalc rsvd FPCdpca

Version History

5 tracked
new 0.4.0 Mar 10, 2026
updated 0.4.0 ← 0.3.0 diff Jan 20, 2026
updated 0.3.0 ← 0.2.0 diff May 8, 2025
updated 0.2.0 ← 0.1.0 diff Apr 9, 2025
new 0.1.0 May 26, 2024