A Bayesian Approach to Event Prediction

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.