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conquer (1.3.3)

Published 2026-02-24 13:47:07 +00:00 by atheaadmin

Installation

Setup this registry in your Rprofile.site file:

options("repos" = c(getOption("repos"), c(gitea="")))

To install the package, run the following command:

install.packages("conquer")

For more information on the CRAN registry, see the documentation.

About this package

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.Convolution-Type Smoothed Quantile Regression

Dependencies

Imports	Rcpp (>= 1.0.3), Matrix, matrixStats, stats
Depends	R (>= 3.5.0)
LinkingTo	Rcpp, RcppArmadillo (>= 0.9.850.1.0)

Details

CRAN

2026-02-24 13:47:07 +00:00

0

GPL-3

Xuming He

Xiaoou Pan

Kean Ming Tan

Wen-Xin Zhou

Project Site

55 KiB

Assets (1)

conquer_1.3.3.tar.gz 55 KiB

Versions (1) View all

1.3.3 2026-02-24