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Perfect simulation of positive Gaussian distributions

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Abstract

We provide an exact simulation algorithm that produces variables from truncated Gaussian distributions on (\(\mathbb{R}\) +)p via a perfect sampling scheme, based on stochastic ordering and slice sampling, since accept-reject algorithms like the one of Geweke (1991) and Robert (1995) are difficult to extend to higher dimensions.

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References

  • Casella G., Lavine M., and Robert C.P. 2001. Explaining the perfect sampler. The American Statistician 55(4): 299–305.

    Google Scholar 

  • Casella G., Mengersen K.L., Robert C.P., and Titterington D.M. 2002. Perfect samplers for mixtures of distributions. J. Royal Statist. Soc. (Ser. B) 64(4): 777–790.

    Google Scholar 

  • Damien P., Wakefield J., and Walker S. 1999. Gibbs sampling for Bayesian non-conjugate and hierarchical models by using auxiliary variables. J. Royal Statist. Soc. (Ser. B) 61: 331–344.

    Google Scholar 

  • Dimakos X. 2001. A guide to exact simulation. Intern. Statist. Rev. 69(1): 27–48.

    Google Scholar 

  • Geweke J. 1991. Efficient simulation from the multivariate normal and student t-distributions subject to linear constraints. Computer Sciences and Statistics: Proc. 23d Symp. Interface, pp. 571–577.

  • Hajivassiliou V.A., McFadden D., and Ruud P.A. 1996. Simulation of multivariate normal rectangle probabilities and their derivatives: Theoretical and computational results. J. Econometrics 72: 85–134.

    Google Scholar 

  • Hobert J.P., Robert C.P., and Titterington D.M. 1999. On perfect simulation for some mixtures of distributions. Statistics and Computing 9: 287–298.

    Google Scholar 

  • Mira A., Møller J., and Roberts G.O. 2001. Perfect slice samplers. J. Royal Statist. Soc. (Ser. B) 63(3): 593–606.

    Google Scholar 

  • Propp J.G. and Wilson D.B. 1996. Exact sampling with coupled Markov chains and applications to statistical mechanics. Random Structures and Algorithms 9: 223–252.

    Google Scholar 

  • Robert C.P. 1995. Simulation of truncated normal variables. Statistics and Computing 5: 121–125.

    Google Scholar 

  • Robert C.P. and Casella G. 1999. Monte Carlo Statistical Methods. Springer Verlag, New York.

    Google Scholar 

  • Wilson D.B. 1998. Annotated bibliography of perfectly random sampling with Markov chains. In: Aldous D. and Propp J. (Eds.), Microsurveys in Discrete Probability, Volume 41 of DIMACS Series in Discrete Mathematics and Theoretical Computer Science, American Mathematical Society, pp. 209–220.

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Philippe, A., Robert, C.P. Perfect simulation of positive Gaussian distributions. Statistics and Computing 13, 179–186 (2003). https://doi.org/10.1023/A:1023264710933

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  • DOI: https://doi.org/10.1023/A:1023264710933

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