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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.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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.