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erboost  

Nonparametric Multiple Expectile Regression via ER-Boost
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("erboost", "1.4")



Attach the package and use:
library("erboost")
Maintained by
Yi Yang
[Scholar Profile | Author Map]
First Published: 2024-01-19
Latest Update: 2024-01-19
Description:
Expectile regression is a nice tool for estimating the conditional expectiles of a response variable given a set of covariates. This package implements a regression tree based gradient boosting estimator for nonparametric multiple expectile regression, proposed by Yang, Y., Qian, W. and Zou, H. (2018) . The code is based on the 'gbm' package originally developed by Greg Ridgeway.
How to cite:
Yi Yang (2024). erboost: Nonparametric Multiple Expectile Regression via ER-Boost. R package version 1.4, https://cran.r-project.org/web/packages/erboost. Accessed 03 Apr. 2025.
Previous versions and publish date:
1.4 (2024-01-19 12:00)
Other packages that cited erboost R package
View erboost citation profile
Other R packages that erboost depends, imports, suggests or enhances
Complete documentation for erboost
Functions, R codes and Examples using the erboost R package
Some associated functions: erboost . erboostject . erboost.perf . plot.erboost . predict.erboost . relative.influence . summary.erboost . 
Some associated R codes: erboost.R .  Full erboost package functions and examples
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