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The method is applicable to a wide range of Markov jump processes and achieves high accuracy, while requiring only a small sample to obtain the importance parameters. We demonstrate its efficiency through benchmark examples in queueing theory and stochastic chemical kinetics.<\/jats:p>","DOI":"10.1017\/s0021900200011645","type":"journal-article","created":{"date-parts":[[2016,3,29]],"date-time":"2016-03-29T14:50:01Z","timestamp":1459263001000},"page":"741-755","source":"Crossref","is-referenced-by-count":0,"title":["Automated State-Dependent Importance Sampling for Markov Jump Processes via Sampling from the Zero-Variance Distribution"],"prefix":"10.1017","volume":"51","author":[{"given":"Adam W.","family":"Grace","sequence":"first","affiliation":[]},{"given":"Dirk P.","family":"Kroese","sequence":"additional","affiliation":[]},{"given":"Werner","family":"Sandmann","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2016,2,19]]},"reference":[{"key":"S0021900200011645_ref18","doi-asserted-by":"publisher","DOI":"10.1145\/1189756.1189758"},{"key":"S0021900200011645_ref20","doi-asserted-by":"publisher","DOI":"10.2307\/1427717"},{"key":"S0021900200011645_ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s101070050099"},{"key":"S0021900200011645_ref15","doi-asserted-by":"publisher","DOI":"10.1145\/566392.566395"},{"key":"S0021900200011645_ref9","doi-asserted-by":"publisher","DOI":"10.1214\/105051607000000122"},{"key":"S0021900200011645_ref14","volume-title":"Handbook of Monte Carlo Methods","year":"2011"},{"key":"S0021900200011645_ref8","doi-asserted-by":"publisher","DOI":"10.1007\/s11134-009-9124-y"},{"key":"S0021900200011645_ref13","doi-asserted-by":"publisher","DOI":"10.1145\/203091.203094"},{"key":"S0021900200011645_ref7","doi-asserted-by":"publisher","DOI":"10.1002\/ett.4460130403"},{"key":"S0021900200011645_ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2012.04.002"},{"key":"S0021900200011645_ref6","doi-asserted-by":"publisher","DOI":"10.1063\/1.3522769"},{"key":"S0021900200011645_ref11","doi-asserted-by":"publisher","DOI":"10.1287\/mnsc.35.11.1367"},{"key":"S0021900200011645_ref5","doi-asserted-by":"publisher","DOI":"10.1016\/0040-5809(72)90022-6"},{"key":"S0021900200011645_ref10","doi-asserted-by":"publisher","DOI":"10.1021\/j100540a008"},{"key":"S0021900200011645_ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s11222-011-9275-7"},{"key":"S0021900200011645_ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.sorms.2011.09.002"},{"key":"S0021900200011645_ref2","volume-title":"Stochastic Simulation: Algorithms and Analysis","year":"2007"},{"key":"S0021900200011645_ref1","volume-title":"Applied Probability and Queues","year":"1987"},{"key":"S0021900200011645_ref26","volume-title":"Stochastic Modeling and the Theory of Queues","year":"1989"},{"key":"S0021900200011645_ref25","volume-title":"Stochastic Processes in Physics and Chemistry","year":"1992"},{"key":"S0021900200011645_ref24","first-page":"260","volume-title":"Proc. 28th Conf. 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