A Bayesian Approach to Event Prediction

M. Antunes, M. A. Amaral Turkman and K. F. Turkman

Journal of Time Series Analysis, 2003, vol. 24, issue 6, 631-646

Abstract: Abstract. In a series of papers, Lindgren (1975a, 1985) and de Maré (1980) set the principles of optimal alarm systems and obtained the basic results. Application of these ideas to linear discrete time‐series models was carried out by Svensson et al. (1996). In this paper, we suggest a Bayesian predictive approach to event prediction and optimal alarm systems for discrete time series. There are two novelties in this approach: first, the variation in the model parameters is incorporated in the analysis; second, this method allows ‘on‐line prediction’ in the sense that, as we observe the process, our posterior probabilities and predictions are updated at each time point.

Date: 2003
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