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

• Autorzy: Showkat Ahmad Dar , Anwar Hassan , Peer Bilal Ahmad , Sameer Ahmad Wani
• Języki publikacji: EN

Abstrakty

EN

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)

Słowa kluczowe

EN

Poisson distribution; Maximum likelihood estimation; Functions

PL

Rozkład Poissona; Metoda największej wiarygodności; Funkcje

• Czasopismo: Statistics in Transition
• Rocznik: 2021
• Tom: 22
• Numer: nr 3
• Strony: 157--174

Twórcy

autor

Showkat Ahmad Dar

• Department of Statistics, University of Kashmir, India

autor

Anwar Hassan

• University of Kashmir, India

autor

Peer Bilal Ahmad

• Department of Mathematical Sciences, Islamic University of Science & Technology, Awantipora, Pulwama, India

autor

Sameer Ahmad Wani

• Department of Statistics, University of Kashmir, India

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Identyfikatory

DOI

10.21307/stattrans-2021-032