Abstract
Segmented line regression has been used in many applications, and the problem of estimating the number of change-points in segmented line regression has been discussed in Kim et al. (2000). This paper studies asymptotic properties of the number of change-points selected by the permutation procedure of Kim et al. (2000). This procedure is based on a sequential application of likelihood ratio type tests, and controls the over-fitting probability by its design. In this paper we show that, under some conditions, the number of change-points selected by the permutation procedure is consistent. Via simulations, the permutation procedure is compared with such information-based criterior as the Bayesian Information Criterion (BIC), the Akaike Information Criterion (AIC), and Generalized Cross Validation (GCV).
Original language | English (US) |
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Pages (from-to) | 597-609 |
Number of pages | 13 |
Journal | Statistica Sinica |
Volume | 19 |
Issue number | 2 |
State | Published - Apr 2009 |
Keywords
- Change-points
- Model selection
- Permutation test
- Segmented line regression
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty