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

  • Frank Kleibergen
  • Herman K. van Dijk
Conference paper
Part of the Statistics and Computing book series (SCO)


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.


matric-variate t (inverted) Wishart triangularisation Simultaneous Equations Model. 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Frank Kleibergen
    • 1
  • Herman K. van Dijk
    • 1
  1. 1.Econometric Institute and Tinbergen InstituteErasmus University RotterdamRotterdamThe Netherlands

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