Bayesian estimation of the number of change points in simple linear regression models

Tsai Hung Fan, Kuo Ching Chang, Chung Bow Lee

研究成果: 雜誌貢獻期刊論文同行評審

2 引文 斯高帕斯(Scopus)

摘要

A Bayesian approach is considered to detect the number of change points in simple linear regression models. A normal-gamma empirical prior for the regression parameters based on maximum likelihood estimator (MLE) is employed in the analysis. Under mild conditions, consistency for the number of change points and boundedness between the estimated location and the true location of the change points are established. The Bayesian approach to the detection of the number of change points is suitable whether the switching simple regression is continuous or discontinuous. Some simulation results are given to confirm the accuracy of the proposed estimator.

原文???core.languages.en_GB???
頁(從 - 到)689-710
頁數22
期刊Communications in Statistics - Theory and Methods
35
發行號4
DOIs
出版狀態已出版 - 2006

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