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.
|Author||Dabao Zhang, Zhongli Jiang, Zeyu Zhang|
|Maintainer||Dabao Zhang <firstname.lastname@example.org>|
|Package repository||View on CRAN|
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