Artikel
EM estimation for the Poisson-Inverse Gamma regression model with varying dispersion: An application to insurance ratemaking
This article presents the Poisson-Inverse Gamma regression model with varying dispersion for approximating heavy-tailed and overdispersed claim counts. Our main contribution is that we develop an Expectation-Maximization (EM) type algorithm for maximum likelihood (ML) estimation of the Poisson-Inverse Gamma regression model with varying dispersion. The empirical analysis examines a portfolio of motor insurance data in order to investigate the efficiency of the proposed algorithm. Finally, both the a priori and a posteriori, or Bonus-Malus, premium rates that are determined by the Poisson-Inverse Gamma model are compared to those that result from the classic Negative Binomial Type I and the Poisson-Inverse Gaussian distributions with regression structures for their mean and dispersion parameters.
- Sprache
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Englisch
- Erschienen in
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Journal: Risks ; ISSN: 2227-9091 ; Volume: 8 ; Year: 2020 ; Issue: 3 ; Pages: 1-23 ; Basel: MDPI
- Klassifikation
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Wirtschaft
- Thema
-
poisson-inverse gamma distribution
em algorithm
regression models for mean and dispersion parameters
motor third party liability insurance
ratemaking
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Tzougas, George
- Ereignis
-
Veröffentlichung
- (wer)
-
MDPI
- (wo)
-
Basel
- (wann)
-
2020
- DOI
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doi:10.3390/risks8030097
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:42 MEZ
Datenpartner
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Objekttyp
- Artikel
Beteiligte
- Tzougas, George
- MDPI
Entstanden
- 2020
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