Abstract
In this article we consider the efficient estimation of the tail distribution of the maximum of correlated normal random variables. We show that the currently recommended Monte Carlo estimator has difficulties in quantifying its precision, because its sample variance estimator is an inefficient estimator of the true variance. We propose a simple remedy: to still use this estimator, but to rely on an alternative quantification of its precision. In addition to this we also consider a completely new sequential importance sampling estimator of the desired tail probability. Numerical experiments suggest that the sequential importance sampling estimator can be significantly more efficient than its competitor.
Original language | English |
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Title of host publication | 2015 Winter Simulation Conference, WSC 2015 |
Publisher | Institute of Electrical and Electronics Engineers, Inc. |
Pages | 633-642 |
Number of pages | 10 |
Volume | 2016-February |
ISBN (Electronic) | 9781467397438 |
DOIs | |
Publication status | Published - 16 Feb 2016 |
Event | Winter Simulation Conference, WSC 2015 - Huntington Beach, United States Duration: 6 Dec 2015 → 9 Dec 2015 |
Conference
Conference | Winter Simulation Conference, WSC 2015 |
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Country/Territory | United States |
City | Huntington Beach |
Period | 6/12/15 → 9/12/15 |
Funding
Zdravko Botev has been supported by the Australian Research Council grant DE140100993. M. Mandjes' research is partly funded by the NWO Gravitation project NETWORKS, grant number 024.002.003.