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Activity Number: 151
Type: Contributed
Date/Time: Monday, August 7, 2006 : 10:30 AM to 12:20 PM
Sponsor: IMS
Abstract - #306224
Title: AIC for Change-Point Models
Author(s): Yoshiyuki Ninomiya*+
Companies: Kyushu University
Address: 6-10-1 Hakozaki, Higashi-ku, Fukuoka, 812-8581, Japan
Keywords: structural change ; model selection ; information criterion ; random walk ; Brownian motion
Abstract:

AIC-type information criterion is generally estimated by the bias-corrected maximum log-likelihood. In regular models, the bias can be estimated by $p$, where $p$ is the number of regular parameters. This presentation considers the AIC-type information criterion for change-point models, which are not regular, the bias of which will not be the same as for regular models. Under some contiguity condition, it is shown that the bias can be evaluated by $3m+p$, where $m$ is the number of change-points, which differs from regular models.

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