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

Showkat Ahmad Dar; Anwar Hassan; Peer Bilal Ahmad; Sameer Ahmad Wani

doi:10.21307/stattrans-2021-032

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

Showkat Ahmad Dar Department of Statistics, University of Kashmir, Srinagar (J&K), India ORCID:https://orcid.org/0000-0002-3661-822X , Anwar Hassan Department of Statistics, University of Kashmir, Srinagar (J&K), India , Peer Bilal Ahmad Department of Mathematical Sciences, Islamic University of Science & Technology, Awantipora, Pulwama (J&K), India , Sameer Ahmad Wani Department of Statistics, University of Kashmir, Srinagar (J&K), India Statistics in Transition new series, vol. 22, 2021, 3, pages: 157–174 Published online: 6 September 2021 DOI 10.21307/stattrans-2021-032

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ARTICLE

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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

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