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SISAM and MIXIN: Two Algorithms for the Computation of Posterior Moments and Densities Using Monte Carlo Integration

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Author Info
Hop, J Peter
Van Dijk, Herman K

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Abstract

Two algorithms and corresponding Fortran computer programs for the computation of posterior moments and densities using the principle of importance sampling are described in detail. The first algorithm makes use of a multivariate Student "t" importance function as approximation of the posterior. It can be applied when the integrand is moderately skew. The second algorithm makes use of a decomposition: a multivariate normal importance function is used to generate directions (lines) and one-dimensional classical quadrature is used to evaluate the integrals defined on the generated lines. The second algorithm can be used in cases where the integrand is possibly very skew in any direction. Citation Copyright 1992 by Kluwer Academic Publishers.

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Publisher Info
Article provided by Springer in its journal Computer Science in Economics & Management.

Volume (Year): 5 (1992)
Issue (Month): 3 (August)
Pages: 183-220
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Handle: RePEc:kap:csecmg:v:5:y:1992:i:3:p:183-220

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  1. L. Bauwens & C.S. Bos & H.K. Van Dijk & R.D. Van Oest, 2002. "Adaptive polar sampling, a class of flexibel and robust Monte Carlo integration methods," Econometric Institute Report 278, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
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  2. L. Bauwens & C.S. Bos & H.K. Van Dijk & R.D. Van Oest, 2003. "Adaptive radial-based direction sampling - some flexibel and robust Monte Carlo integration methods," Econometric Institute Report 327, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
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