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標題: Bayesian estimation of the number of change points in simple linear regression models
作者: Fan, T.H.
Chang, K.C.
Lee, C.B.
關鍵字: Bayesian estimation;change points;consistency;linear regression;random-variables;sequence;regimes
Project: Communications in Statistics-Theory and Methods
期刊/報告no:: Communications in Statistics-Theory and Methods, Volume 35, Issue 4, Page(s) 689-710.
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.
ISSN: 0361-0926
DOI: 10.1080/03610920500498881
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