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Ing and Lai (2011) <doi:10.5705/ss.2010.081> proposed a high-dimensional model selection procedure that comprises three steps: orthogonal greedy algorithm (OGA), high-dimensional information criterion (HDIC), and Trim. The first two steps, OGA and HDIC, are used to sequentially select input variables and determine stopping rules, respectively. The third step, Trim, is used to delete irrelevant variables remaining in the second step. This package aims at fitting a high-dimensional linear regression model via OGA+HDIC+Trim.

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conda 45.1 kB | noarch/r-ohit-1.0.0-r43h142f84f_0.tar.bz2  1 year and 2 months ago 24 main
conda 44.7 kB | noarch/r-ohit-1.0.0-r42h142f84f_0.tar.bz2  2 years and 9 months ago 59 main
conda 44.7 kB | noarch/r-ohit-1.0.0-r36h6115d3f_0.tar.bz2  5 years and 22 days ago 118 main

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