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conquer
View on CRAN: Click
here
Download and install conquer package within the R console
Install from CRAN:
install.packages("conquer")
Install from Github:
library("remotes")
install_github("cran/conquer")
Install by package version:
library("remotes")
install_version("conquer", "1.3.3")
Attach the package and use:
library("conquer")
Maintained by
Xiaoou Pan
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-04-15
Latest Update: 2023-03-06
Description:
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.
How to cite:
Xiaoou Pan (2020). conquer: Convolution-Type Smoothed Quantile Regression. R package version 1.3.3, https://cran.r-project.org/web/packages/conquer. Accessed 22 Dec. 2024.
Previous versions and publish date:
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Complete documentation for conquer
Functions, R codes and Examples using
the conquer R package
Some associated functions: conquer-package . conquer.cv.reg . conquer . conquer.process . conquer.reg .
Some associated R codes: RcppExports.R . conquer-package.R . generate_ns.R . smqr.R . Full conquer package functions and examples
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