Robust regression trees based on m-estimators

Giuliano Galimberti (), Marilena Pillati () and Gabriele Soffritti ()

Statistica, 2007, vol. 67, issue 2, 173-190

Abstract: The paper addresses the problem of robustness of regression trees with respect to outlying data. New robust tree-based procedures are described, which are obtained by introducing in the tree building phase some objective functions already used in the linear robust regression approach, namely Huber’s and Tukey’s bisquare functions. The performance of the new procedures is evaluated through a Monte Carlo experiment.

Date: 2007
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Persistent link: https://EconPapers.repec.org/RePEc:bot:rivsta:v:67:y:2007:i:2:p:173-190

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