quantreg. nonpar: An R Package for performing nonparametric series quantile regression
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Published version
Accepted manuscript
Date
2016
DOI
Authors
Lipsitz, Michael
Belloni, Alexandre
Chernozhukov, Victor
Fernández-Val, Iván
Version
Published and Accepted manuscript versions.
OA Version
Citation
M Lipsitz, A Belloni, V Chernozhukov, I Fernández-Val. "quantreg. nonpar: An R Package for Performing Nonparametric Series Quantile Regression." The R Journal (2016) 8:2, pp. 370-381.
Abstract
The R package quantreg.nonpar implements nonparametric quantile regression methods to estimate and make inference on partially linear quantile models. quantreg.nonpar obtains point estimates of the conditional quantile function and its derivatives based on series approximations to the nonparametric part of the model. It also provides pointwise and uniform confidence intervals over a region of covariate values and/or quantile indices for the same functions using analytical and resampling methods. This paper serves as an introduction to the package and displays basic functionality of the functions contained within.
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This article is licensed under a Creative Commons Attribution 3.0 Unported license.