Efficient Computer Generation of Matric-Variate t Drawings with an Application to Bayesian Estimation of Simple Market Models
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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.
Keywordsmatric-variate t (inverted) Wishart triangularisation Simultaneous Equations Model.
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