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PDF Availablehttps://doi.org/10.1111/j.1468-0262.2008.00839.x
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Cite Journal: Econometrica |  Publication Date: Mar 1, 2008 |
 Citations: 20 |
Affiliation: Kyoto University, University of Melbourne
We study a Monte Carlo algorithm for computing marginal and stationary densities of stochastic models with the Markov property, establishing global asymptotic normality and OP(n–1/2) convergence. Asymptotic normality is used to derive error bounds in terms of the distribution of the norm deviation.
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