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Summary Statistics for Endpoint-Conditioned Continuous-Time Markov Chains
2011
Journal of Applied Probability
Continuous-time Markov chains are a widely used modelling tool. Applications include DNA sequence evolution, ion channel gating behaviour, and mathematical finance. We consider the problem of calculating properties of summary statistics (e.g. mean time spent in a state, mean number of jumps between two states, and the distribution of the total number of jumps) for discretely observed continuous-time Markov chains. Three alternative methods for calculating properties of summary statistics are
doi:10.1239/jap/1324046009
fatcat:vpv2oibbhff6fjvsi7kfudmvku