
AbstractWe extend the construction principle of phase-type (PH) distributions to allow for inhomogeneous transition rates and show that this naturally leads to direct probabilistic descriptions of certain transformations of PH distributions. In particular, the resulting matrix distributions enable the carrying over of fitting properties of PH distributions to distributions with heavy tails, providing a general modelling framework for heavy-tail phenomena. We also illustrate the versatility and parsimony of the proposed approach in modelling a real-world heavy-tailed fire insurance dataset.
Applications of statistics to actuarial sciences and financial mathematics, product integral, heavy tail, Markov processes: estimation; hidden Markov models, Probability (math.PR), Point estimation, inhomogeneous phase-type, matrix Pareto distribution, matrix Weibull distribution, FOS: Mathematics, Probability distributions: general theory, Inhomogeneous phase-type, Mathematics - Probability, Continuous-time Markov processes on discrete state spaces
Applications of statistics to actuarial sciences and financial mathematics, product integral, heavy tail, Markov processes: estimation; hidden Markov models, Probability (math.PR), Point estimation, inhomogeneous phase-type, matrix Pareto distribution, matrix Weibull distribution, FOS: Mathematics, Probability distributions: general theory, Inhomogeneous phase-type, Mathematics - Probability, Continuous-time Markov processes on discrete state spaces
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