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) |
|---|---|
| Pages (from-to) | 51-57 |
| Number of pages | 7 |
| Journal | Journal of Applied Statistics |
| Volume | 25 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 1 1976 |