hdpca: Principal Component Analysis in High-Dimensional Data
Version 1.0.0

In high-dimensional settings: Estimate the number of distant spikes based on the Generalized Spiked Population (GSP) model. Estimate the population eigenvalues, angles between the sample and population eigenvectors, correlations between the sample and population PC scores, and the asymptotic shrinkage factors. Adjust the shrinkage bias in the predicted PC scores.

Getting started

Package details

AuthorRounak Dey, Seunggeun Lee
Date of publication2016-08-02 09:13:22
MaintainerRounak Dey <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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hdpca documentation built on May 29, 2017, 1 p.m.