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政大機構典藏 > 商學院 > 風險管理與保險學系 > 會議論文 > Item 140.119/75486

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/75486

Title:	New estimators for parallel steady-state simulations
Authors:	Hsieh, Minghua;Glynn, P.W. 謝明華
Contributors:	風管系
Keywords:	Gaussians;Initial conditions;Model selection criteria;Parallel discrete event simulations;Schwarz;Steady state parameter;Steady-state simulations;Test problem;Time averages;Time points;Discrete event simulation;Estimation
Date:	2009-12
Issue Date:	2015-06-01 17:47:25 (UTC+8)
Abstract:	When estimating steady-state parameters in parallel discrete event simulation, initial transient is an important issue to consider. To mitigate the impact of initial condition on the quality of the estimator, we consider a class of estimators obtained by putting different weights on the sampling average across replications at selected time points. The weights are chosen to maximize their Gaussian likelihood. Then we apply model selection criterion due to Akaike and Schwarz to select two of them as our proposed estimators. In terms of relative root MSE, the proposed estimators compared favorably to the standard time average estimator in a typical test problem with significant initial transient. ©2009 IEEE.
Relation:	Proceedings - Winter Simulation Conference,469-474
Data Type:	conference
DOI 連結:	http://dx.doi.org/10.1109/WSC.2009.5429354
DOI:	10.1109/WSC.2009.5429354
Appears in Collections:	[風險管理與保險學系] 會議論文

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