The R Journal: accepted article

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SIQR: An R Package for Single-index Quantile Regression PDF download
Tianhai Zu and Yan Yu

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, (1.7 Kb)
CRAN packages: quantreg, KernSmooth
CRAN Task Views implied by cited CRAN packages: Econometrics, Environmetrics, Multivariate, Optimization, ReproducibleResearch, Robust, SocialSciences, Survival


CC BY 4.0
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://journal.r-project.org/archive/2021/RJ-2021-092/index.html}
}