quantreg.nonpar: an R package for performing nonparametric series quantile regression
Name
RJ-2016-052.pdf
Description
Published version
Size
722.53 KB
Format
Adobe PDF
Checksum (MD5)
8f32e54985d673e4c79664502a1b2615
Author(s)
Lipsitz, Michael
Belloni, Alexandre
Chernozhukov, Victor V
Fernandez-Val, Ivan
Alternative Title
Quantreg.nonpar: an R package for performing nonparametric series quantile regression
Date Issued
June 2017
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
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.
MIT Department
Massachusetts Institute of Technology. Department of Economics
Terms of Use
Creative Commons Attribution 3.0 unported license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1920/wp.cem.2017.2917
