The R Journal: article published in 2021, volume 13:2

SIQR: An R Package for Single-index Quantile Regression
Tianhai Zu and Yan Yu , The R Journal (2021) 13:2, pages 460-470.

Abstract We develop an R package SIQR that implements the single-index quantile regression (SIQR) models via an efficient iterative local linear approach in Wu et al. (2010). Single-index quantile regression models are important tools in semiparametric regression to provide a comprehensive view of the conditional distributions of a response variable. It is especially useful when the data is heterogeneous or heavy-tailed. The package provides functions that allow users to fit SIQR models, predict, provide standard errors of the single-index coefficients via bootstrap, and visualize the estimated univariate function. We apply the R package SIQR to a well-known Boston Housing data.

Received: 2021-01-15; online 2021-10-19, supplementary material, (1.6 KiB)
CRAN packages: quantreg, KernSmooth
CRAN Task Views implied by cited CRAN packages: Econometrics, Environmetrics, Multivariate, Optimization, ReproducibleResearch, Robust, SocialSciences, Survival

This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2021-092,
  author = {Tianhai Zu and Yan Yu},
  title = {{SIQR: An R Package for Single-index Quantile Regression}},
  year = {2021},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2021-092},
  url = {https://doi.org/10.32614/RJ-2021-092},
  pages = {460--470},
  volume = {13},
  number = {2}
}