Abstract
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.
Original language | English |
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Pages (from-to) | 443-450 |
Number of pages | 8 |
Journal | Econometrica |
Volume | 76 |
Issue number | 2 |
DOIs | |
Publication status | Published - Mar 2008 |
Externally published | Yes |