PCDimension
Finding the Number of Significant Principal Components
v1.1.14
·
Apr 7, 2025
·
Apache License (== 2.0)
Description
Implements methods to automate the Auer-Gervini graphical Bayesian approach for determining the number of significant principal components. Automation uses clustering, change points, or simple statistical models to distinguish "long" from "short" steps in a graph showing the posterior number of components as a function of a prior parameter. See <doi:10.1101/237883>.
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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
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1.1.14
Mar 10, 2026