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on Econometrics |
| By: | M.P. Wiper,; F.J. Giron; A. Pewsey |
| Abstract: | In this article we consider approaches to Bayesian inference for the half-normal and half-t distributions. We show that a generalized version of the normal-gamma distribution is conjugate to the half-normal likelihood and give the moments of this new distribution. The bias and coverage of the Bayesian posterior mean estimator of the halfnormal location parameter are compared with those of maximum likelihood based estimators. Inference for the half-t distribution is performed using Gibbs sampling and model comparison is carried out using Bayes factors. A real data example is presented which demonstrates the fitting of the half-normal and half-t models. |
| Date: | 2005–07 |
| URL: | http://d.repec.org/n?u=RePEc:cte:wsrepe:ws054709&r=ecm |
| By: | Kim C. Border (California Institute of Technology); Paolo Ghirardato (Università da Torino); Uzi Segal (Boston College) |
| Abstract: | This note shows that if the space of events is sufficiently rich and the subjective probability function of each individual is non-atomic, then there is a sigma-algebra of events over which everyone will have the same probability function, and moreover, the range of these probabilities is the whole [0, 1] segment. |
| Date: | 2005–08–02 |
| URL: | http://d.repec.org/n?u=RePEc:boc:bocoec:616&r=ecm |