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• W2045803758 abstract "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 dataset; (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 be effectively visualized and that subject-matter scientists are used to analyzing and interpreting." @default.
• W2045803758 created "2016-06-24" @default.
• W2045803758 creator A5014873408 @default.
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• W2045803758 date "2008-06-01" @default.
• W2045803758 modified "2023-10-11" @default.
• W2045803758 title "Model-Based Recursive Partitioning" @default.
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• W2045803758 doi "https://doi.org/10.1198/106186008x319331" @default.
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