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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Tanachot Chaito | en_US |
dc.contributor.author | Pimwarat Nanthaprut | en_US |
dc.contributor.author | Nawapon Nakharutai | en_US |
dc.contributor.author | Manad Khamkong | en_US |
dc.date.accessioned | 2022-05-27T08:34:46Z | - |
dc.date.available | 2022-05-27T08:34:46Z | - |
dc.date.issued | 2022-04-01 | en_US |
dc.identifier.issn | 23510676 | en_US |
dc.identifier.issn | 16859057 | en_US |
dc.identifier.other | 2-s2.0-85127764531 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85127764531&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/73042 | - |
dc.description.abstract | In this study, we introduce a new class of length-biased distribution called the length-biased Gamma-Rayleigh (LBGR) distribution. Various mathematical properties, including its limit th behavior, the r moment, the moment generating function, the survival function, and the hazard ratio function, are derived. Maximum-likelihood estimation is used to estimate the parameters of the LBGR distribution. Three environmental datasets were used in a comparison of distributions to determine which one could best fit the data. The results indicate that the LBGR distribution provided a better fit than the Rayleigh, lognormal, gamma, and gamma-Rayleigh distributions. | en_US |
dc.subject | Mathematics | en_US |
dc.title | The Length-Biased Gamma-Rayleigh Distribution with Applications | en_US |
dc.type | Journal | en_US |
article.title.sourcetitle | Thailand Statistician | en_US |
article.volume | 20 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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