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Bayesian quantile additive regression trees

2016-07-10Code Available0· sign in to hype

Bereket P. Kindo, Hao Wang, Timothy Hanson, Edsel A. Peña

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Abstract

Ensemble of regression trees have become popular statistical tools for the estimation of conditional mean given a set of predictors. However, quantile regression trees and their ensembles have not yet garnered much attention despite the increasing popularity of the linear quantile regression model. This work proposes a Bayesian quantile additive regression trees model that shows very good predictive performance illustrated using simulation studies and real data applications. Further extension to tackle binary classification problems is also considered.

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