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The Negative Binomial-Generalized Lindley Distribution for Overdispersed Data

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dc.contributor.author Atikankul Y.
dc.contributor.author Wattanavisut A.
dc.contributor.author Liu S.
dc.contributor.other Srinakharinwirot University
dc.date.accessioned 2023-11-15T01:54:30Z
dc.date.available 2023-11-15T01:54:30Z
dc.date.issued 2022
dc.identifier.uri https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144924028&doi=10.1134%2fS1995080222120058&partnerID=40&md5=26603cd5b90a19a24f63a572e8362e3b
dc.identifier.uri https://ir.swu.ac.th/jspui/handle/123456789/29096
dc.description.abstract Abstract: In this paper, a new count distribution for overdispersed data is introduced. The distribution is a mixture of the negative binomial and generalized Lindley distributions. This new distribution contains the negative binomial-Lindley distribution as a special case. Some statistical properties are studied. The parameters estimation procedure is obtained by the method of maximum likelihood. Simulation studies are performed to assess the performance of the maximum likelihood estimators. Finally, real overdispersed data sets are analyzed to show the usefulness of the distribution. © 2022, Pleiades Publishing, Ltd.
dc.publisher Pleiades Publishing
dc.subject generalized Lindley distribution
dc.subject maximum likelihood estimation
dc.subject mixed negative binomial distribution
dc.subject overdispersion
dc.subject generalized Lindley distribution
dc.subject maximum likelihood estimation
dc.subject mixed negative binomial distribution
dc.subject overdispersion
dc.title The Negative Binomial-Generalized Lindley Distribution for Overdispersed Data
dc.type Article
dc.rights.holder Scopus
dc.identifier.bibliograpycitation Lobachevskii Journal of Mathematics. Vol 43, No.9 (2022), p.2378-2386
dc.identifier.doi 10.1134/S1995080222120058


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