Package: erboost 1.4

erboost: Nonparametric Multiple Expectile Regression via ER-Boost

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) <doi:10.1080/00949655.2013.876024>. The code is based on the 'gbm' package originally developed by Greg Ridgeway.

Authors:Yi Yang [aut, cre], Hui Zou [aut], Greg Ridgeway [ctb, cph]

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10 exports 0.09 score 1 dependencies 1 scripts 166 downloads

Last updated 8 months agofrom:056c604cd5. Checks:OK: 9. Indexed: yes.

Exports:erboosterboost.fiterboost.losserboost.moreerboost.perfpermutation.test.erboostplot.erboostpredict.erboostrelative.influencesummary.erboost

Dependencies:lattice