Ohit

OGA+HDIC+Trim and High-Dimensional Linear Regression Models

CRAN Package

Ing and Lai (2011) 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.

  • Version1.0.0
  • R versionunknown
  • LicenseGPL-2
  • Needs compilation?No
  • Last release09/06/2017

Team


Insights

Last 30 days

Last 365 days

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Data provided by cranlogs


Binaries


Dependencies

  • Imports1 package