• Medientyp: E-Artikel
  • Titel: A new count data model applied in the analysis of vaccine adverse events and insurance claims
  • Beteiligte: Dar, Showkat Ahmad [VerfasserIn]; Hassan, Anwar [VerfasserIn]; Ahmad, Peer Bilal [VerfasserIn]; Wani, Sameer Ahmad [VerfasserIn]
  • Erschienen: New York: Exeley, 2021
  • Sprache: Englisch
  • DOI: https://doi.org/10.21307/stattrans-2021-032
  • ISSN: 2450-0291
  • Schlagwörter: maximum likelihood estimation ; compound distribution ; count data ; weighted exponential distribution ; poisson distribution
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  • Beschreibung: The clustering of their letter shapes is performed based on the pairwise distances between their topological signatures.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.
  • Zugangsstatus: Freier Zugang
  • Rechte-/Nutzungshinweise: Namensnennung - Nicht-kommerziell - Keine Bearbeitung (CC BY-NC-ND)