Alternative robust estimation methods for parameters of Gumbel distribution: an application to wind speed data with outliers

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dc.authoridAYDIN, Demet/0000-0002-3491-8392
dc.contributor.authorAydin, Demet
dc.date.accessioned2025-03-23T19:30:32Z
dc.date.available2025-03-23T19:30:32Z
dc.date.issued2018
dc.departmentSinop Üniversitesi
dc.description.abstractAn accurate determination of wind speed distribution is the basis for an evaluation of the wind energy potential required to design a wind turbine, so it is important to estimate unknown parameters of wind speed distribution. In this paper, Gumbel distribution is used in modelling wind speed data, and alternative robust estimation methods to estimate its parameters are considered. The methodologies used to obtain the estimators of the parameters are least absolute deviation, weighted least absolute deviation, median/MAD and least median of squares. The performances of the estimators are compared with traditional estimation methods (i.e., maximum likelihood and least squares) according to bias, mean square deviation and total mean square deviation criteria using a Monte-Carlo simulation study for the data with and without outliers. The simulation results show that least median of squares and median/MAD estimators are more efficient than others for data with outliers in many cases. However, median/MAD estimator is not consistent for location parameter of Gumbel distribution in all cases. In real data application, it is firstly demonstrated that Gumbel distribution fits the daily mean wind speed data well and is also better one to model the data than Weibull distribution with respect to the root mean square error and coefficient of determination criteria. Next, the wind data modified by outliers is analysed to show the performance of the proposed estimators by using numerical and graphical methods.
dc.identifier.doi10.12989/was.2018.26.6.383
dc.identifier.endpage395
dc.identifier.issn1226-6116
dc.identifier.issn1598-6225
dc.identifier.issue6
dc.identifier.scopus2-s2.0-85049332850
dc.identifier.scopusqualityQ2
dc.identifier.startpage383
dc.identifier.urihttps://doi.org/10.12989/was.2018.26.6.383
dc.identifier.urihttps://hdl.handle.net/11486/5100
dc.identifier.volume26
dc.identifier.wosWOS:000434469200004
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorAydin, Demet
dc.language.isoen
dc.publisherTechno-Press
dc.relation.ispartofWind and Structures
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250323
dc.subjectGumbel distribution
dc.subjectleast absolute deviation
dc.subjectmedian/MAD estimator
dc.subjectMonte-Carlo simulation
dc.subjectwind speed data
dc.titleAlternative robust estimation methods for parameters of Gumbel distribution: an application to wind speed data with outliers
dc.typeArticle

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