A New Count Data Model Applied in the Analysis of Vaccine Adverse Events and Insurance Claims

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

doi:10.21307/stattrans-2021-032

Author

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

Title

A New Count Data Model Applied in the Analysis of Vaccine Adverse Events and Insurance Claims

Source

Statistics in Transition, 2021, vol. 22, nr 3, s. 157-174, tab., wykr., bibliogr. 14 poz.

Keyword

Rozkład Poissona, Metoda największej wiarygodności, Funkcje
Poisson distribution, Maximum likelihood estimation, Functions

Note

summ.

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.(original abstract)

Accessibility

The Main Library of the Cracow University of Economics
The Library of Warsaw School of Economics
The Library of University of Economics in Katowice

Full text

Bibliography

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Cited by

ISSN

1234-7655

Language

eng

URI / DOI

BazEkon - The Main Library of the Cracow University of Economics

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