Loading...
Please wait, while we are loading the content...
Similar Documents
MARKOV CHAIN MONTE CARLO CONFIDENCE INTERVALS (2014)
| Content Provider | CiteSeerX |
|---|---|
| Author | Atchadé, Yves F. |
| Abstract | Abstract. For a reversible and ergodic Markov chain {Xn, n ≥ 0} with invariant distribution pi, we show that a valid confidence interval for pi(h) can be constructed whenever the asymptotic variance σ2P (h) is finite and positive. We do not impose any additional condition on the convergence rate of the Markov chain. The confidence interval is derived using the so-called fixed-b lag-window estimator of σ2P (h). We also derive a result that suggests that the proposed confidence interval procedure converges faster than classical confidence interval procedures based on the Gaussian distribution and standard central limit theorems for Markov chains. |
| File Format | |
| Publisher Date | 2014-01-01 |
| Access Restriction | Open |
| Subject Keyword | Markov Chain Ergodic Markov Chain Xn Invariant Distribution Pi Asymptotic Variance Valid Confidence Interval Confidence Interval Procedure Standard Central Limit Theorem So-called Fixed-b Lag-window Estimator Convergence Rate Additional Condition Confidence Interval Gaussian Distribution Classical Confidence Interval Procedure |
| Content Type | Text |
| Resource Type | Article |
