Principal Component Analysis in High-Dimensional Data

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) .


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install.packages("hdpca")

1.1.5 by Rounak Dey, 14 days ago


Browse source code at https://github.com/cran/hdpca


Authors: Rounak Dey , Seunggeun Lee


Documentation:   PDF Manual  


GPL (>= 2) license


Imports lpSolve, boot


See at CRAN