The Zero-adjusted Inverse Gaussian distribution as a model for insurance claims.

Gillian Heller, Dimitrios Stasinopoulos, Robert Rigby

    Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

    Abstract

    We introduce a method for modelling insurance claim sizes, including zero claims. A mixed discrete-continuous model, with a probability mass at zero and an Inverse Gaussian continuous component, is used. The Inverse Gaussian distribution accommodates the extreme right skewness of the claim distribution. The model explicitly speci¯es a logit-linear model for the occurrence of a claim; and log-linear models for the mean claim size (given a claim has occurred); and the dispersion of claim sizes (given a claim has occurred). The method is illustrated on aa Australian motor vehicle insurance data set.
    Original languageEnglish
    Title of host publicationProceedings of the 21st international workshop on statistical modelling
    EditorsJohn Hinde, Jochen Einbeck, John Newell
    Place of PublicationGalway, Ireland
    PublisherStatistical Modelling Society
    Pages226-233
    Number of pages8
    ISBN (Print)1862201803
    Publication statusPublished - 2006
    EventInternational Workshop on Statistical Modelling (21st : 2006) - Galway, Ireland
    Duration: 3 Jul 20067 Jul 2006

    Workshop

    WorkshopInternational Workshop on Statistical Modelling (21st : 2006)
    CityGalway, Ireland
    Period3/07/067/07/06

    Keywords

    • Inverse Gaussian model
    • zero-adjusted
    • insurance claims
    • gamlss

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