Bayesian inference for clustered extremes
Bayesian inference for extremal index, mean cluster size and other cluster functionals of extremes in a dependent stationary sequence is considered. A Metropolis-Hastings sampler is described for sampling from the posterior distribution of parameters. Performance of the algorithm is investigated on simulated data. An application to a wind speed data is presented.
scientific article; zbMATH DE number 5520599