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hdpca
View on CRAN: Click
here
Download and install hdpca package within the R console
Install from CRAN:
install.packages("hdpca")
Install from Github:
library("remotes")
install_github("cran/hdpca") Install by package version:
library("remotes")
install_version("hdpca", "1.1.5") Attach the package and use:
library("hdpca")
Maintained by
Rounak Dey
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-08-02
Latest Update: 2021-01-13
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) .
How to cite:
Rounak Dey (2016). hdpca: Principal Component Analysis in High-Dimensional Data. R package version 1.1.5, https://cran.r-project.org/web/packages/hdpca. Accessed 25 Jun. 2026.
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Complete documentation for hdpca
Functions, R codes and Examples using
the hdpca R package
Some associated functions: hdpc_est . pc_adjust . select.nspike .
Some associated R codes: pca_functions.R . Full hdpca package functions and examples
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