A Tapered Pareto-Poisson Model for Extreme Pyroclastic Flows: Application to the Quantification of Volcano Hazards
This paper intends to discuss the problems of parameter estimation in a proposed tapered Pareto-Poisson model for the assessment of large pyroclastic flows, which are essential in quantifying the size and risk of volcanic hazards. In dealing with the tapered Pareto distribution, the paper applies both maximum likelihood estimation and a Bayesian framework with objective priors and Metropolis algorithm. The techniques are further illustrated by an example of modeling extreme flow volumes at Soufriere Hills Volcano, and their simulation results are addressed.
Random Walk Metropolis
Tapered Pareto Distribution
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