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KERE  

Expectile Regression in Reproducing Kernel Hilbert Space
View on CRAN: Click here


Download and install KERE package within the R console
Install from CRAN:
install.packages("KERE")

Install from Github:
library("remotes")
install_github("cran/KERE")

Install by package version:
library("remotes")
install_version("KERE", "1.0.0")



Attach the package and use:
library("KERE")
Maintained by
Yi Yang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-08-28
Latest Update: 2015-08-28
Description:
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.
How to cite:
Yi Yang (2015). KERE: Expectile Regression in Reproducing Kernel Hilbert Space. R package version 1.0.0, https://cran.r-project.org/web/packages/KERE. Accessed 10 Mar. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited KERE R package
View KERE citation profile
Other R packages that KERE depends, imports, suggests or enhances
Complete documentation for KERE
Functions, R codes and Examples using the KERE R package
Some associated functions: KERE . as.kernelMatrix . cv.KERE . dots . kernel-class . kernelMatrix . plot.KERE . predict.KERE . 
Some associated R codes: KERE.R . aobjects.R . cv.KERE.R . kernelmatrix.R . kernels.R . plot.KERE.R . predict.KERE.R . utilities.R .  Full KERE package functions and examples
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