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Computer Intensive Methods in Statistics pp 30–46Cite as

Efficient Computer Generation of Matric-Variate t Drawings with an Application to Bayesian Estimation of Simple Market Models

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Part of the book series: Statistics and Computing ((SCO))

Abstract

Algorithms for efficient computer generation of matric-variate t random drawings are constructed which make use of two results in distribution theory. First, the definition of a matric-variate t distributed random matrix as the product of a matric-variate normal distributed random matrix and the square root of an inverted-Wishart distributed random matrix. Second, a decomposition of the Wishart and inverted Wishart matrix into triangular matrices. The different steps of the algorithm for matric-variate t drawings and the decomposition of the (inverted-) Wishart are explained. For illustrative purposes, the posterior density of the structural parameters of a simple market model is evaluated. These structural parameters are nonlinear functions of matric-variate t variables.

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Author information

Authors and Affiliations

  1. Econometric Institute and Tinbergen Institute, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR, Rotterdam, The Netherlands

    Frank Kleibergen & Herman K. van Dijk

Authors
  1. Frank Kleibergen
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  2. Herman K. van Dijk
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Editor information

Editors and Affiliations

  1. Institut für Statistik und Ökonometrie, Wirtschaftswissenschaftliche Fakultät, Humboldt-Universität zu Berlin, Spandauer Straße 1, O-1020, Berlin, Germany

    Wolfgang Härdle

  2. Institute de Statistique, Université Catholique de Louvain, B-1348, Louvain-la-Neuve, Belgium

    Léopold Simar

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© 1993 Springer-Verlag Berlin Heidelberg

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Kleibergen, F., van Dijk, H.K. (1993). Efficient Computer Generation of Matric-Variate t Drawings with an Application to Bayesian Estimation of Simple Market Models. In: Härdle, W., Simar, L. (eds) Computer Intensive Methods in Statistics. Statistics and Computing. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-52468-4_2

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  • DOI: https://doi.org/10.1007/978-3-642-52468-4_2

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-0677-9

  • Online ISBN: 978-3-642-52468-4

  • eBook Packages: Springer Book Archive

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