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Efficient and accurate approximate Bayesian inference with an application to insurance data

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  • Streftaris, George
  • Worton, Bruce J.

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  • Streftaris, George & Worton, Bruce J., 2008. "Efficient and accurate approximate Bayesian inference with an application to insurance data," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2604-2622, January.
    • Handle: RePEc:eee:csdana:v:52:y:2008:i:5:p:2604-2622
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    References listed on IDEAS

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    1. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
    2. S. P. Brooks & P. Giudici & G. O. Roberts, 2003. "Efficient construction of reversible jump Markov chain Monte Carlo proposal distributions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 3-39, January.
    3. Ioannis Ntzoufras & Athanassios Katsis & Dimitris Karlis, 2005. "Bayesian Assessment of the Distribution of Insurance Claim Counts Using Reversible Jump MCMC," North American Actuarial Journal, Taylor & Francis Journals, vol. 9(3), pages 90-108.
    4. P. Damlen & J. Wakefield & S. Walker, 1999. "Gibbs sampling for Bayesian non‐conjugate and hierarchical models by using auxiliary variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(2), pages 331-344, April.
    5. Czado, Claudia & Delwarde, Antoine & Denuit, Michel, 2005. "Bayesian Poisson log-bilinear mortality projections," Insurance: Mathematics and Economics, Elsevier, vol. 36(3), pages 260-284, June.
    6. Candel, Math J.J.M., 2007. "Empirical Bayes estimators of the random intercept in multilevel analysis: Performance of the classical, Morris and Rao version," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 3027-3040, March.
    7. Ainsworth, L.M. & Dean, C.B., 2006. "Approximate inference for disease mapping," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2552-2570, June.
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    Cited by:

    1. Pierre-Olivier Goffard & Patrick Laub, 2021. "Approximate Bayesian Computations to fit and compare insurance loss models," Post-Print hal-02891046, HAL.
    2. Goffard, Pierre-Olivier & Laub, Patrick J., 2021. "Approximate Bayesian Computations to fit and compare insurance loss models," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 350-371.

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