CRAN

OHPL 1.4

Ordered Homogeneity Pursuit Lasso for Group Variable Selection

Released May 18, 2019 by Nan Xiao

This package cannot yet be used with Renjin it depends on other packages which are not available: glmnet 2.0-18 An older version of this package is more compatible with Renjin.

Dependencies

glmnet 2.0-18 pls 2.7-1 mvtnorm 1.0-11

Ordered homogeneity pursuit lasso (OHPL) algorithm for group variable selection proposed in Lin et al. (2017) . The OHPL method exploits the homogeneity structure in high-dimensional data and enjoys the grouping effect to select groups of important variables automatically. This feature makes it particularly useful for high-dimensional datasets with strongly correlated variables, such as spectroscopic data.

Source

R

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