<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Burnetas, AN</style></author><author><style face="normal" font="default" size="100%">Katehakis, M.N.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">On confidence intervals from simulation of finite Markov chains</style></title><secondary-title><style face="normal" font="default" size="100%">Mathematical Methods of Operations Research</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Computational methods</style></keyword><keyword><style  face="normal" font="default" size="100%">computer simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Convergence of numerical methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Discrete Markov chains</style></keyword><keyword><style  face="normal" font="default" size="100%">Markov processes</style></keyword><keyword><style  face="normal" font="default" size="100%">probability</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1997</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.scopus.com/inward/record.uri?eid=2-s2.0-5244337928&amp;partnerID=40&amp;md5=a83a32ba20367981ce961984137644fd</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">46</style></volume><pages><style face="normal" font="default" size="100%">241-250</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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.</style></abstract><notes><style face="normal" font="default" size="100%">cited By 1</style></notes></record></records></xml>