Monte Carlo Comparison of the Parameter Estimation Methods for the Two-Parameter Gumbel Distribution

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dc.authoridAYDIN, Demet/0000-0002-3491-8392
dc.contributor.authorAydin, Demet
dc.contributor.authorSenoglu, Birdal
dc.date.accessioned2025-03-23T19:27:10Z
dc.date.available2025-03-23T19:27:10Z
dc.date.issued2015
dc.departmentSinop Üniversitesi
dc.description.abstractThe performances of the seven different parameter estimation methods for the Gumbel distribution are compared with numerical simulations. Estimation methods used in this study are the method of moments (ME), the method of maximum likelihood (ML), the method of modified maximum likelihood (MML), the method of least squares (LS), the method of weighted least squares (WLS), the method of percentile (PE) and the method of probability weighted moments (PWM). Performance of the estimators is compared with respect to their biases, MSE and deficiency (Def) values via Monte-Carlo simulation. A Monte Carlo Simulation study showed that the method of PWM was the best performance the other methods of bias criterion and the method of ML outperforms the other methods in terms of Def criterion. A real life example taken from the hydrology literature is given at the end of the paper.
dc.identifier.doi10.22237/jmasm/1446351060
dc.identifier.endpage140
dc.identifier.issn1538-9472
dc.identifier.issue2
dc.identifier.scopus2-s2.0-84951756535
dc.identifier.scopusqualityQ4
dc.identifier.startpage123
dc.identifier.urihttps://doi.org/10.22237/jmasm/1446351060
dc.identifier.urihttps://hdl.handle.net/11486/4858
dc.identifier.volume14
dc.identifier.wosWOS:000445695200009
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherWayne State Univ Press
dc.relation.ispartofJournal of Modern Applied Statistical Methods
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20250323
dc.subjectGumbel distribution
dc.subjectestimation methods
dc.subjectMonte Carlo simulation
dc.subjectefficiency
dc.titleMonte Carlo Comparison of the Parameter Estimation Methods for the Two-Parameter Gumbel Distribution
dc.typeArticle

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