Slash Maxwell Distribution: Definition, Modified Maximum Likelihood Estimation and Applications
dc.authorid | Acitas, Sukru/0000-0002-4131-0086 | |
dc.authorscopusid | 40460949100 | |
dc.authorscopusid | 57524658600 | |
dc.authorscopusid | 6506973358 | |
dc.authorwosid | Senoglu, Birdal/Aag-9300-2020 | |
dc.authorwosid | Arslan, Talha/B-9217-2013 | |
dc.authorwosid | Acitas, Sukru/O-5507-2018 | |
dc.contributor.author | Acitas, Sukru | |
dc.contributor.author | Arslan, Talha | |
dc.contributor.author | Senoglu, Birdal | |
dc.date.accessioned | 2025-05-10T17:34:53Z | |
dc.date.available | 2025-05-10T17:34:53Z | |
dc.date.issued | 2020 | |
dc.department | T.C. Van Yüzüncü Yıl Üniversitesi | en_US |
dc.department-temp | [Acitas, Sukru] Eskisehir Tech Univ, Dept Stat, TR-26470 Eskisehir, Turkey; [Arslan, Talha] Van Yuzuncu Yil Univ, Dept Econometr, TR-65080 Van, Turkey; [Senoglu, Birdal] Ankara Univ, Dept Stat, TR-06100 Ankara, Turkey | en_US |
dc.description | Acitas, Sukru/0000-0002-4131-0086 | en_US |
dc.description.abstract | In this study slash Maxwell (SM) distribution, defined as a ratio of a Maxwell random variate to a power of an independent uniform random variate, is introduced. Its stochastic representation and some distributional properties such as moments, skewness and kurtosis measures are provided. The maximum likelihood (ML) method is used for estimating the unknown parameters. However, closed forms of the ML estimators cannot be obtained since the likelihood equations include nonlinear functions of the unknown parameters. We therefore use Tiku's (1967,1968) modified maximum likelihood (MML) methodology which allows to obtain explicit forms of the estimators. Some asymptotic properties of the MML estimators are derived. A Monte-Carlo simulation study is also carried out to compare the performances of the ML and MML estimators. Two data sets taken from the literature are modelled using the SM distribution in application part of the study. | en_US |
dc.description.woscitationindex | Emerging Sources Citation Index | |
dc.identifier.doi | 10.35378/gujs.539929 | |
dc.identifier.endpage | 263 | en_US |
dc.identifier.issn | 2147-1762 | |
dc.identifier.issue | 1 | en_US |
dc.identifier.scopus | 2-s2.0-85086759161 | |
dc.identifier.scopusquality | Q3 | |
dc.identifier.startpage | 249 | en_US |
dc.identifier.trdizinid | 362571 | |
dc.identifier.uri | https://doi.org/10.35378/gujs.539929 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14720/13947 | |
dc.identifier.volume | 33 | en_US |
dc.identifier.wos | WOS:000519536100019 | |
dc.identifier.wosquality | N/A | |
dc.language.iso | en | en_US |
dc.publisher | Gazi Univ | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Maxwell | en_US |
dc.subject | Slashing Methodology | en_US |
dc.subject | Stochastic Representation | en_US |
dc.subject | Modified Maximum Likelihood | en_US |
dc.title | Slash Maxwell Distribution: Definition, Modified Maximum Likelihood Estimation and Applications | en_US |
dc.type | Article | en_US |