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Two methods of fitting piecewise multiple regression models are presented. One, based on dynamic programming, yields maximum‐likelihood estimators and is suitable for sequences of moderate length. A second, hierarchical, procedure yields approximations to the maximum‐likelihood estimators and is suitable for very long sequences of data. Both methods have computational requirements that are linear in the number of segments.
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Douglas M. Hawkins (1976) studied this question.
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