The estimation of phase-type related functionals using Markov chain Monte Carlo methods

Authors: Bladt M.; Gonzalez A.; Lauritzen S.L.

Source: Scandinavian Actuarial Journal, Volume 2003, Number 4, October 2003 , pp. 280-300(21)

Publisher: Routledge, part of the Taylor & Francis Group

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Abstract:

In this paper we present a method for estimation of functionals depending on one or several phase-type distributions. This could for example be the ruin probability in a risk reserve process where claims are assumed to be of phase-type. The proposed method uses a Markov chain Monte Carlo simulation to reconstruct the Markov jump processes underlying the phase-type variables in combination with Gibbs sampling to obtain a stationary sequence of phase-type probability measures from the posterior distribution of these given the observations. This enables us to find quantiles of posterior distributions of functionals of interest, thereby representing estimation uncertainty in a flexible way. We compare our estimates to those obtained by the method of maximum likelihood and find a good agreement. We illustrate the statistical potential of the method by estimating ruin probabilities in simulated examples.

Keywords: Bayesian analysis; Markov chain monte carlo; phase-type distribution; ruin probabilities

Document Type: Research article

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