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An Algorithm for the Computation of Posterior Moments and Densities Using Simple Importance Sampling

Herman K. Van Dijk, J. Peter Hop and Adri S. Louter
Journal of the Royal Statistical Society. Series D (The Statistician)
Vol. 36, No. 2/3, Special Issue: Practical Bayesian Statistics (1987), pp. 83-90
Published by: Wiley for the Royal Statistical Society
DOI: 10.2307/2348500
Stable URL: http://www.jstor.org/stable/2348500
Page Count: 8
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An Algorithm for the Computation of Posterior Moments and Densities Using Simple Importance Sampling
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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 densities of the parameters of interest of econometric models. In the present paper we describe the computational steps of one Monte Carlo method, which is known in the literature as importance sampling. Further, a set of standard programs is available, which may be used for the implementation of a simple case of importance sampling. The computer programs have been written in FORTRAN 77.

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