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.
Econometrics, Environmetrics, Multivariate, Optimization, ReproducibleResearch, Robust, SocialSciences, Survival
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For attribution, please cite this work as
Zu & Yu, "The R Journal: SIQR: An R Package for Single-index Quantile Regression", The R Journal, 2021
BibTeX citation
@article{RJ-2021-092,
author = {Zu, Tianhai and Yu, Yan},
title = {The R Journal: SIQR: An R Package for Single-index Quantile Regression},
journal = {The R Journal},
year = {2021},
note = {https://doi.org/10.32614/RJ-2021-092},
doi = {10.32614/RJ-2021-092},
volume = {13},
issue = {2},
issn = {2073-4859},
pages = {460-470}
}