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Estimating Claim Size and Probability in the Auto-insurance Industry: the Zero-adjusted Inverse Gaussian (ZAIG) Distribution

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  • Bortoluzzo, Adriana B.
  • Claro, Danny P.
  • Caetano, Marco Antonio L. & Artes, Rinaldo

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  • Bortoluzzo, Adriana B. & Claro, Danny P. & Caetano, Marco Antonio L. & Artes, Rinaldo, 2009. "Estimating Claim Size and Probability in the Auto-insurance Industry: the Zero-adjusted Inverse Gaussian (ZAIG) Distribution," Insper Working Papers wpe_175, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    • Handle: RePEc:ibm:ibmecp:wpe_175
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    References listed on IDEAS

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    1. Weisberg, Herbert I & Tomberlin, Thomas J & Chatterjee, Sangit, 1984. "Predicting Insurance Losses under Cross-Classification: A Comparison of Alternative Approaches," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(2), pages 170-178, April.
    2. Smyth, Gordon K. & Jørgensen, Bent, 2002. "Fitting Tweedie's Compound Poisson Model to Insurance Claims Data: Dispersion Modelling," ASTIN Bulletin, Cambridge University Press, vol. 32(1), pages 143-157, May.
    3. de Jong,Piet & Heller,Gillian Z., 2008. "Generalized Linear Models for Insurance Data," Cambridge Books, Cambridge University Press, number 9780521879149, January.
    4. King, Gary & Zeng, Langche, 2001. "Logistic Regression in Rare Events Data," Political Analysis, Cambridge University Press, vol. 9(2), pages 137-163, January.
    5. Stasinopoulos, D. Mikis & Rigby, Robert A., 2007. "Generalized Additive Models for Location Scale and Shape (GAMLSS) in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 23(i07).
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