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Examples of fitting structured phase–type distributions
63
Citations
19
References
1994
Year
Phase TransitionsDensity EstimationEngineeringPhysicsPhase–type DistributionsGibbs MeasureHidden Markov ModelStochastic ProcessesMarkov KernelStochastic AnalysisProbability TheoryProbabilistic Wave ModellingTransient StatesMarkov Chain Monte CarloStatisticsRich ClassStochastic Modeling
Abstract A sub–class of phase–type distributions is defined in terms of a Markov process with sequential transitions between transient states and transitions from these states to absorption. Such distributions form a very rich class; they can be fitted to data, and any structure revealed by the parameter estimates used to develop more parsimonious re–parametrizations. Several example data sets are used as illustrations.
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