quantreg.nonpar: Nonparametric Series Quantile Regression

Implements the nonparametric quantile regression method developed by Belloni, Chernozhukov, and Fernandez-Val (2011) to partially linear quantile models. Provides point estimates of the conditional quantile function and its derivatives based on series approximations to the nonparametric part of the model. Provides pointwise and uniform confidence intervals using analytic and resampling methods.

Version: 1.0
Depends: R (≥ 2.10), quantreg, mnormt, fda, Rearrangement
Published: 2016-04-01
Author: Michael Lipsitz, Alexandre Belloni, Victor Chernozhukov, Ivan Fernandez-Val
Maintainer: Ivan Fernandez-Val <ivanf at bu.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: quantreg.nonpar results

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Reference manual: quantreg.nonpar.pdf
Package source: quantreg.nonpar_1.0.tar.gz
Windows binaries: r-devel: quantreg.nonpar_1.0.zip, r-release: quantreg.nonpar_1.0.zip, r-oldrel: quantreg.nonpar_1.0.zip
OS X El Capitan binaries: r-release: quantreg.nonpar_1.0.tgz
OS X Mavericks binaries: r-oldrel: quantreg.nonpar_1.0.tgz

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