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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "conquer" in publications use:'
type: software
license: GPL-3.0-only
title: 'conquer: Convolution-Type Smoothed Quantile Regression'
version: 1.3.3
doi: 10.32614/CRAN.package.conquer
abstract: Estimation and inference for conditional linear quantile regression models
  using a convolution smoothed approach. In the low-dimensional setting, efficient
  gradient-based methods are employed for fitting both a single model and a regression
  process over a quantile range. Normal-based and (multiplier) bootstrap confidence
  intervals for all slope coefficients are constructed. In high dimensions, the conquer
  method is complemented with flexible types of penalties (Lasso, elastic-net, group
  lasso, sparse group lasso, scad and mcp) to deal with complex low-dimensional structures.
authors:
- family-names: He
  given-names: Xuming
  email: xmhe@umich.edu
- family-names: Pan
  given-names: Xiaoou
  email: xip024@ucsd.edu
- family-names: Tan
  given-names: Kean Ming
  email: keanming@umich.edu
- family-names: Zhou
  given-names: Wen-Xin
  email: wez243@ucsd.edu
repository: https://CRAN.R-project.org/package=conquer
repository-code: https://github.com/XiaoouPan/conquer
url: https://github.com/XiaoouPan/conquer
date-released: '2023-03-05'
contact:
- family-names: Pan
  given-names: Xiaoou
  email: xip024@ucsd.edu