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quantreg.nonpar: an R package for performing nonparametric series quantile regression

Author(s)
Lipsitz, Michael; Belloni, Alexandre; Chernozhukov, Victor V; Fernandez-Val, Ivan
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Alternative title
Quantreg.nonpar: an R package for performing nonparametric series quantile regression
Terms of use
Creative Commons Attribution 3.0 unported license https://creativecommons.org/licenses/by/3.0/
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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.
Date issued
2017-06
URI
https://hdl.handle.net/1721.1/122791
Journal
cennmap
Publisher
Economic & Social Research Council
Citation
Lipsitz, Michael et al. "Quantreg.nonpar: an R package for performing nonparametric series quantile regression." cennmap (June 2017): CWP29/17
Version: Final published version

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