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.

Getting started

Package details

AuthorDabao Zhang, Zhongli Jiang, Zeyu Zhang
MaintainerDabao Zhang <zhangdb@purdue.edu>
Package repositoryView on CRAN
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POCRE documentation built on May 2, 2019, 8:33 a.m.