Consider a finite state irreducible Markov reward chain. It is shown that there exist simulation estimates and confidence intervals for the expected first passage times and rewards as well as the expected average reward, with 100% coverage probability. The length of the confidence intervals converges to zero with probability one as the sample size increases; it also satisfies a large deviations property.
|Original language||English (US)|
|Number of pages||10|
|Journal||Mathematical Methods of Operations Research|
|State||Published - 1997|
All Science Journal Classification (ASJC) codes
- Management Science and Operations Research
- Discrete Markov Chains