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)|
|Number of pages||7|
|Journal||Journal of Applied Statistics|
|State||Published - Jan 1 1976|