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erboost (version 1.4)

Nonparametric Multiple Expectile Regression via ER-Boost

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.

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Version

Install

install.packages('erboost')

Monthly Downloads

141

Version

1.4

License

GPL-3

Maintainer

Last Published

January 19th, 2024

Functions in erboost (1.4)

erboost

ER-Boost Expectile Regression Modeling
summary.erboost

Summary of a erboost object
relative.influence

Methods for estimating relative influence
erboost.object

ER-Boost Expectile Regression Model Object
plot.erboost

Marginal plots of fitted erboost objects
predict.erboost

Predict method for erboost Model Fits
erboost.perf

erboost performance