BAYESIAN DETECTION OF STRUCTURAL CHANGES

NOBUHISA KASHIWAGI

The Institute of Statistical Mathematics, 4-6-7 Minami-Azabu, Minato-ku, Tokyo 106, Japan

(Received November 16, 1988; revised February 21, 1990)

Abstract. A Bayesian solution is given to the problem of making inferences about an unknown number of structural changes in a sequence of observations. Inferences are based on the posterior distribution of the number of change points and on the posterior probabilities of possible change points. Detailed analyses are given for binomial data and some regression problems, and numerical illustrations are provided. In addition, an approximation procedure to compute the posterior probabilities is presented.

Key words and phrases: Bayesian inference, change point, predictive log likelihood, Lindisfarne scribes problem, regression.