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On sampling the degree-of-freedom of Student's-t disturbances

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  • Watanabe, Toshiaki

Abstract

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%.

Suggested Citation

  • Watanabe, Toshiaki, 2001. "On sampling the degree-of-freedom of Student's-t disturbances," Statistics & Probability Letters, Elsevier, vol. 52(2), pages 177-181, April.
    • Handle: RePEc:eee:stapro:v:52:y:2001:i:2:p:177-181
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    References listed on IDEAS

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    1. 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.
    2. Geweke, John, 1994. "Priors for Macroeconomic Time Series and Their Application," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 609-632, August.
    3. Geweke, J, 1993. "Bayesian Treatment of the Independent Student- t Linear Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 19-40, Suppl. De.
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