geogria/QICD: Estimate the Coefficients for Non-Convex Penalized Quantile Regression Model by using QICD Algorithm
Version 1.1.1

Extremely fast algorithm "QICD", Iterative Coordinate Descent Algorithm for High-dimensional Nonconvex Penalized Quantile Regression. This algorithm combines the coordinate descent algorithm in the inner iteration with the majorization minimization step in the outside step. For each inner univariate minimization problem, we only need to compute a one-dimensional weighted median, which ensures fast computation. Tuning parameter selection is based on two different method: the cross validation and BIC for quantile regression model. Details are described in the Peng,B and Wang,L. (2015) linked to via the URL below with .

Getting started

Package details

AuthorBo Peng [aut, cre], Rondall E. Jones [ctb], John A. Wisniewski [ctb]
Date of publication2016-05-30 06:29:37
MaintainerBo Peng <[email protected]>
LicenseGPL-2
Version1.1.1
URL http://www.tandfonline.com/doi/abs/10.1080/10618600.2014.913516#.VsoK-JMrJp8
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("geogria/QICD")
geogria/QICD documentation built on May 14, 2017, 8:49 a.m.