title: SELECTING THE NUMBER OF CHANGE-POINTS IN SEGMENTED LINE REGRESSION.
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).
authors.affiliation: Syracuse University, National Institute of Aging, and National Cancer Institute.
authors.forename: Hyune-Ju
authors.initials: HJ
authors.lastname: Kim
authors.forename: Binbing
authors.initials: B
authors.lastname: Yu
authors.forename: Eric J
authors.initials: EJ
authors.lastname: Feuer