Inference on parameters of a geometric process with scaled muth distribution

dc.contributor.authorBicer C.
dc.contributor.authorBakouch H.S.
dc.contributor.authorBicer H.D.
dc.date.accessioned2021-01-14T18:11:22Z
dc.date.available2021-01-14T18:11:22Z
dc.date.issued2020
dc.departmentKKÜ
dc.description.abstractThe problem of statistical modeling of the geometric count data with a specific probability model of lifetimes is of interest and importance in reliability. In this paper, we construct a geometric process (GP), with parameter a, for modeling the geometric count data when the distribution of first occurrence time is a scaled Muth with parameters ? and ?. We investigate the estimators of the process parameters a, ? and ? from a point of approximations of classical and modified approach by using the different estimation methodologies such as the maximum likelihood, moments, least-squares and maximum spacing. We perform a simulation study to compare the estimation performance of the estimators obtained. Finally, we provide an illustrative analysis conducted on a real-world dataset to show the e±ciency of the GP model constructed in this paper against the alpha-series and renewal processes and exemplify the data modeling stages. Consequently, a forecasting to such data using the GP with the scaled Muth is investigated. © 2020 World Scientific Publishing Company.en_US
dc.identifier.doi10.1142/S0219477521500061
dc.identifier.issn0219-4775
dc.identifier.scopus2-s2.0-85093529066
dc.identifier.scopusquality#YOK
dc.identifier.urihttps://doi.org/10.1142/S0219477521500061
dc.identifier.urihttps://hdl.handle.net/20.500.12587/12965
dc.identifier.wosWOS:000613387100007
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherWorld Scientificen_US
dc.relation.ispartofFluctuation and Noise Letters
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectData modelingen_US
dc.subjectEstimation methodsen_US
dc.subjectGeometric processen_US
dc.subjectMonotonic processen_US
dc.subjectTrending successive inter-arrival timesen_US
dc.titleInference on parameters of a geometric process with scaled muth distributionen_US
dc.typeArticle

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