POCRE: Penalized Orthogonal-Components Regression

Penalized orthogonal-components regression (POCRE) is a supervised dimension reduction method for high-dimensional data. It sequentially constructs orthogonal components (with selected features) which are maximally correlated to the response residuals. POCRE can also construct common components for multiple responses and thus build up latent-variable models.

Version: 0.6.0
Imports: stats, utils, ggplot2 (≥ 2.2.0), pracma, EbayesThresh
Published: 2022-03-16
Author: Dabao Zhang, Zhongli Jiang, Zeyu Zhang, Yu-ting Chen
Maintainer: Dabao Zhang <zhangdb at purdue.edu>
License: GPL-2
NeedsCompilation: no
CRAN checks: POCRE results


Reference manual: POCRE.pdf


Package source: POCRE_0.6.0.tar.gz
Windows binaries: r-devel: POCRE_0.6.0.zip, r-release: POCRE_0.6.0.zip, r-oldrel: POCRE_0.6.0.zip
macOS binaries: r-release (arm64): POCRE_0.6.0.tgz, r-oldrel (arm64): POCRE_0.6.0.tgz, r-release (x86_64): POCRE_0.6.0.tgz, r-oldrel (x86_64): POCRE_0.6.0.tgz
Old sources: POCRE archive


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