KERE: Expectile Regression in Reproducing Kernel Hilbert Space

An efficient algorithm inspired by majorization-minimization principle for solving the entire solution path of a flexible nonparametric expectile regression estimator constructed in a reproducing kernel Hilbert space.

Version:	1.0.0
Depends:	methods
Published:	2015-08-28
DOI:	10.32614/CRAN.package.KERE
Author:	Yi Yang, Teng Zhang, Hui Zou
Maintainer:	Yi Yang <yiyang at umn.edu>
License:	GPL-2
NeedsCompilation:	yes
CRAN checks:	KERE results

Documentation:

Reference manual:

KERE.html , KERE.pdf

Downloads:

Package source:	KERE_1.0.0.tar.gz
Windows binaries:	r-devel: KERE_1.0.0.zip, r-release: KERE_1.0.0.zip, r-oldrel: KERE_1.0.0.zip
macOS binaries:	r-release (arm64): KERE_1.0.0.tgz, r-oldrel (arm64): KERE_1.0.0.tgz, r-release (x86_64): KERE_1.0.0.tgz, r-oldrel (x86_64): KERE_1.0.0.tgz

Linking:

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