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dc.contributor.authorManad Khamkongen_US
dc.contributor.authorPachitjianut Siripanichen_US
dc.date.accessioned2018-09-04T10:09:12Z-
dc.date.available2018-09-04T10:09:12Z-
dc.date.issued2015-01-01en_US
dc.identifier.issn01252526en_US
dc.identifier.other2-s2.0-84934765689en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84934765689&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/54188-
dc.description.abstract© 2015 Chiang Mai University. All rights reserved. Poisson distribution is well used as a standard model for analyzing count data. Tests based on the index of dispersion (ID) concerning the variance and the mean are not able to discriminate between the Poisson distribution and some others. An alternative method for the test that data comes from Poisson distribution are proposed based on skewness properties, which is the same as coefficient of variation properties. Monte Carlo studies show that the proposed tests are powerful competitor to the ID tests when alternative distribution is not Poisson but its variance is close to the mean.en_US
dc.subjectBiochemistry, Genetics and Molecular Biologyen_US
dc.subjectChemistryen_US
dc.subjectMaterials Scienceen_US
dc.subjectMathematicsen_US
dc.subjectPhysics and Astronomyen_US
dc.titleAlternative tests for the poisson distributionen_US
dc.typeJournalen_US
article.title.sourcetitleChiang Mai Journal of Scienceen_US
article.volume42en_US
article.stream.affiliationsChiang Mai Universityen_US
article.stream.affiliationsThailand National Institute of Development Administrationen_US
Appears in Collections:CMUL: Journal Articles

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