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An Algorithm For The Computation Of Posterior Moments And Densities Using Simple Importance Sampling

Author

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  • van Dijk, H. K.
  • Hop, J. P.
  • Louter, A. S.

Abstract

In earlier work (van Dijk (1984, Chapter 3)) one of the authors discussed the use of Monte Carlo integration methods for the computation of the multivariate integrals that are defined in the posterior moments and the liosterior densities of the parameters of interest of econometric models. In the present paper we describe the computational steps of one Monte Carlo method, mentioned In that work, which is known in the literature as importance sampling. Further, we have prepared a set of standard programs, which may be used for the implementation of a simple case of importance sampling. The computer programs have been written in Fortran.

Suggested Citation

  • van Dijk, H. K. & Hop, J. P. & Louter, A. S., 1986. "An Algorithm For The Computation Of Posterior Moments And Densities Using Simple Importance Sampling," Econometric Institute Archives 272354, Erasmus University Rotterdam.
    • Handle: RePEc:ags:eureia:272354
    DOI: 10.22004/ag.econ.272354
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    References listed on IDEAS

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    1. Geweke, John, 1986. "Exact Inference in the Inequality Constrained Normal Linear Regression Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(2), pages 127-141, April.
    2. Van Dijk, Herman K. & Kloek, Teun & Boender, C. Guus E., 1985. "Posterior moments computed by mixed integration," Journal of Econometrics, Elsevier, vol. 29(1-2), pages 3-18.
    3. van Dijk, H. K. & Kloek, T., 1980. "Further experience in Bayesian analysis using Monte Carlo integration," Journal of Econometrics, Elsevier, vol. 14(3), pages 307-328, December.
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    Cited by:

    1. Samer A. Kharroubi, 2018. "Posterior simulation via the exponentially tilted signed root log-likelihood ratio," Computational Statistics, Springer, vol. 33(1), pages 213-234, March.
    2. Baştürk, Nalan & Grassi, Stefano & Hoogerheide, Lennart & Opschoor, Anne & van Dijk, Herman K., 2017. "The R Package MitISEM: Efficient and Robust Simulation Procedures for Bayesian Inference," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i01).
    3. van Dijk, H. K., 1987. "Some Advances In Bayesian Estimation Methods Using Monte Carlo Integration," Econometric Institute Archives 272361, Erasmus University Rotterdam.
    4. Hop, J. P. & van Duk, H. K., 1990. "Two Algorithms For The Computation Of Posterior Moments And Densities Using Monte Carlo Integration," Econometric Institute Archives 272483, Erasmus University Rotterdam.

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