Title

Maximum Likelihood Regression Trees

Keywords

CART; Information criteria; Pruning trees; Tree size selection

Abstract

We propose a method of constructing regression trees within the framework of maximum likelihood. It inherits the backward fitting idea of classification and regression trees (CART) but has more rigorous justification. Simulation studies show that it provides more accurate tree model selection compared to CART. The analysis of a baseball dataset is given as an illustration.

Publication Date

9-1-2004

Publication Title

Journal of Computational and Graphical Statistics

Volume

13

Issue

3

Number of Pages

586-598

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1198/106186004X2165

Socpus ID

4344681291 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/4344681291

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