Statistical model selection based on Bayes decision theory and its application to change detection problem

被引：1

作者：

Gotoh, M ^{[1
]}

Hirasawa, S ^{[1
]}

机构：

[1] Waseda Univ, Sch Sci & Engn, Dept Ind & Management Syst Engn, Shinjuku Ku, Tokyo 169, Japan

来源：

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS | 1999年 / 60-1卷

关键词：

statistical model selection; change detection problem; Bayesian statistics; information criteria;

D O I：

10.1016/S0925-5273(98)00186-8

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The statistical model selection problems are discussed, and the criterion based on the Bayes decision theory for the detection of the true model is derived. We propose a new Bayesian model selection scheme, which can detect the change points of the parameter of the information source and also estimate each unknown parameter. In this paper, we formulate the Bayes optimal solution of the change detection problem, and analyze its property of the consistency. (C) 1999 Elsevier Science B.V. All rights reserved.

引用

页码：629 / 638

页数：10

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