Package: hdpca
Type: Package
Title: Principal Component Analysis in High-Dimensional Data
Version: 1.1.5
Date: 2021-01-13
Author: Rounak Dey, Seunggeun Lee
Maintainer: Rounak Dey <deyrnk@umich.edu>
Description: 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.
	Dey, R. and Lee, S. (2019) <doi:10.1016/j.jmva.2019.02.007>.
Depends: R (>= 3.0.0)
License: GPL (>= 2)
Repository: CRAN
Imports: lpSolve, boot
NeedsCompilation: no
Packaged: 2021-01-13 17:31:08 UTC; Rounak
Date/Publication: 2021-01-13 18:40:07 UTC
Built: R 4.6.0; ; 2026-04-26 19:41:22 UTC; unix
