Abstract
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.
Original language | English (US) |
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Pages (from-to) | 51-57 |
Number of pages | 7 |
Journal | Journal of Applied Statistics |
Volume | 25 |
Issue number | 1 |
DOIs | |
State | Published - 1976 |
Externally published | Yes |