conquer: Convolution-Type Smoothed Quantile Regression

Fast and accurate convolution-type smoothed quantile regression. Implemented using Barzilai-Borwein gradient descent with a Huber regression warm start. Construct confidence intervals for regression coefficients using multiplier bootstrap.

Version: 1.0.2
Depends: R (≥ 3.5.0)
Imports: Rcpp (≥ 1.0.3), Matrix, matrixStats, stats
LinkingTo: Rcpp, RcppArmadillo (≥ 0.9.850.1.0)
Published: 2020-08-27
Author: Xuming He [aut], Xiaoou Pan [aut, cre], Kean Ming Tan [aut], Wen-Xin Zhou [aut]
Maintainer: Xiaoou Pan <xip024 at ucsd.edu>
License: GPL-3
URL: https://github.com/XiaoouPan/conquer
NeedsCompilation: yes
SystemRequirements: C++11
Materials: README
CRAN checks: conquer results

Downloads:

Reference manual: conquer.pdf
Package source: conquer_1.0.2.tar.gz
Windows binaries: r-devel: conquer_1.0.2.zip, r-release: conquer_1.0.2.zip, r-oldrel: conquer_1.0.2.zip
macOS binaries: r-release: conquer_1.0.2.tgz, r-oldrel: conquer_1.0.2.tgz
Old sources: conquer archive

Reverse dependencies:

Reverse imports: quantreg

Linking:

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