Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/70703
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dc.contributor.authorTheerapong Kaewpraserten_US
dc.contributor.authorManad Khamkongen_US
dc.date.accessioned2020-10-14T08:39:41Z-
dc.date.available2020-10-14T08:39:41Z-
dc.date.issued2020-07-01en_US
dc.identifier.issn23510676en_US
dc.identifier.issn16859057en_US
dc.identifier.other2-s2.0-85087355123en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85087355123&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/70703-
dc.description.abstract© 2020, Thai Statistical Association. All rights reserved. In this paper, we propose an alternative method for estimating generalized exponential distributions by applying plotting positions of modified percentile estimates. We compared its efficiency with the classical maximum likelihood estimator and percentile estimator in terms of root mean square errors. Simulation results show that the percentile estimator outperformed the others for small sample sizes while the proposed estimator was most effective for medium to large sample sizes. This finding was supported by applying the proposed estimator to deduce whether Thai rainy season rainfall data followed a generalized exponential distribution from a rain gauging station in Fang district, Chiang Mai Province, Thailand.en_US
dc.subjectMathematicsen_US
dc.titleAn alternative estimator with appropriate plotting position estimates for the generalized exponential distributionen_US
dc.typeJournalen_US
article.title.sourcetitleThailand Statisticianen_US
article.volume18en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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