Antithetic Acceleration of Monte Carlo Integration in Bayesian Inference

Elsevier Science Publishers B.V.
Publication Type:
Journal Article
Journal of Econometrics, 1988, 38 (1-2), pp. 73 - 90
Issue Date:
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2008008349OK.pdf946.48 kB
Adobe PDF
It is proposed to sample antithetically rather than randomly from the posterior density in Bayesian inference using Monte Carlo integration. Conditions are established under which the number of replications required with antithetic sampling relative to the number required with random sampling is inversely proportional to sample size, as sample size increases. The result is illustrated in an experiment using a bivariate vector autoregression.
Please use this identifier to cite or link to this item: