Quotation Zeileis, Achim, Hothorn, Torsten, Hornik, Kurt. 2008. Model-based Recursive Partitioning. Journal of Computational and Graphical Statistics 17 (2): 492-514.




Recursive partitioning is embedded into the general and well-established class of parametric models that can be fitted using M-type estimators (including maximum likelihood). An algorithm for model-based recursive partitioning is suggested for which the basic steps are: (1) fit a parametric model to a data set, (2) test for parameter instability over a set of partitioning variables, (3) if there is some overall parameter instability, split the model with respect to the variable associated with the highest instability, (4) repeat the procedure in each of the daughter nodes. The algorithm yields a partitioned (or segmented) parametric model that can effectively be visualized and that subject-matter scientists are used to analyze and interpret.


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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Journal of Computational and Graphical Statistics
Citation Index SCI
WU-Journal-Rating new FIN-A, VW-C
Language English
Title Model-based Recursive Partitioning
Volume 17
Number 2
Year 2008
Page from 492
Page to 514
Reviewed? Y
URL http://epub.wu.ac.at/dyn/virlib/wp/eng/mediate/epub-wu-01_86e.pdf?ID=epub-wu-01_86e


Zeileis, Achim (Former researcher)
Hornik, Kurt (Details)
Hothorn, Torsten (Germany)
Institute for Statistics and Mathematics IN (Details)
Research Institute for Computational Methods FI (Details)
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