We consider quantile estimation using Markov chain Monte Carlo and establish conditions under which the sampling distribution of the Monte Carlo error is approximately Normal. Further, we investigate techniques to estimate the associated asymptotic variance, which enables construction of an asymptotically valid interval estimator. Finally, we ex- plore the finite sample properties of these methods through examples and provide some recommendations to practitioners.
Bibliographical notePublisher Copyright:
© 2014, Institute of Mathematical Statistics. All rights reserved.
- Batch means
- Central limit theorem
- Markov chain
- Monte carlo
- Quantile estimation