On sampling the degree-of-freedom of Student's-t disturbances
In a Bayesian analysis of a model with Student's-t disturbances developed by Geweke (J. Appl. Econom. 8 (1993) S19), and Fernández and Steel (J. Amer. Statist. Assoc. 93 (1998) 359), the degree-of-freedom of Student's-t disturbances, if unknown, must be sampled from its conditional distribution. This article presents a new method for this sampling using a Metropolis-Hastings acceptance-rejection algorithm proposed by Tierney (Ann. Statist. 21 (1994) 1701). The acceptance probabilities in both the acceptance-rejection and Metropolis-Hastings parts of this method are shown to exceed 95%.
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Volume (Year): 52 (2001)
Issue (Month): 2 (April)
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References listed on IDEAS
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- Chib, Siddhartha & Greenberg, Edward, 1994. "Bayes inference in regression models with ARMA (p, q) errors," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 183-206.
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