Model-Based Rules for Describing Recurrent Events
Don Harding, Adrian Pagan · Princeton University Press eBooks · 2016
The chapter discusses a particular way of producing rules to summarize the nature of the recurrent events. These rules come from the idea that the data incorporating the recurrent event can be captured by models that specify a number of regimes, and then using the information provided by the fitted model to date the recurrent event. The chapter discusses variants of Markov switching models in the context where there is only a single series in which the recurrent event is observed. It then deals with dating cycles with univariate series. Finally, it considers model-based rules for dating events with multivariate series.