A new count data model applied in the analysis of vaccine adverse events and insurance claims

Dar Showkat Ahmad (), Hassan Anwar, Ahmad Peer Bilal and Wani Sameer Ahmad
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Dar Showkat Ahmad: Department of Statistics, University of Kashmir, Srinagar (J&K), India .
Hassan Anwar: Department of Statistics, University of Kashmir, Srinagar (J&K), India .
Ahmad Peer Bilal: Department of Mathematical Sciences, Islamic University of Science & Technology, Awantipora, Pulwama (J&K), India .
Wani Sameer Ahmad: Department of Statistics, University of Kashmir, Srinagar (J&K), India .

Statistics in Transition New Series, 2021, vol. 22, issue 3, 157-174

Abstract: The article presents a new probability distribution, created by compounding the Poisson distribution with the weighted exponential distribution. Important mathematical and statistical properties of the distribution have been derived and discussed. The paper describes the proposed model’s parameter estimation, performed by means of the maximum likelihood method. Finally, real data sets are analyzed to verify the suitability of the proposed distribution in modeling count data sets representing vaccine adverse events and insurance claims.

Keywords: poisson distribution; weighted exponential distribution; compound distribution; count data; maximum likelihood estimation. (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:stintr:v:22:y:2021:i:3:p:157-174:n:1

DOI: 10.21307/stattrans-2021-032

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