A simulation-based hyperparameter selection for quantile estimation of the generalized extreme value distribution

Jeong-Soo Park

Mathematics and Computers in Simulation (MATCOM), 2005, vol. 70, issue 4, 227-234

Abstract: A systematic way of selecting hyperparameters of the prior on the shape parameter of the generalized extreme value distribution (GEVD) is presented. The optimal selection is based on a Monte Carlo simulation in the generalized maximum likelihood estimation (GMLE) framework. A scaled total misfit measure for the accurate estimation of upper quantiles is used for the selection criterion. The performance evaluations for GEVD and non-GEVD show that the GMLE with selected hyperparameters produces more accurate quantile estimates than the MLE, the L-moments estimator, and Martins–Stedinger’s GMLE.

Keywords: Beta distribution; Hydrology; Maximum likelihood estimation; L-moment estimation; Penalized likelihood; Shape parameter (search for similar items in EconPapers)
Date: 2005
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:70:y:2005:i:4:p:227-234

DOI: 10.1016/j.matcom.2005.09.003

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