DocumentCode :
2615079
Title :
Low bias integrated path estimators
Author :
Calvin, James M.
Author_Institution :
New Jersey Inst. of Technol., Newark
fYear :
2007
fDate :
9-12 Dec. 2007
Firstpage :
303
Lastpage :
307
Abstract :
We consider the problem of estimating the time-average variance constant for a stationary process. A previous paper described an approach based on multiple integrations of the simulation output path, and described the efficiency improvement that can result compared with the method of batch means (which is a special case of the method). In this paper we describe versions of the method that have low bias for moderate simulation run lengths. The method constructs an estimator based on applying a quadratic function to the simulation output. The particular quadratic form is chosen to minimize variance subject to constraints on the order of the bias. Estimators that are first-order and second-order unbiased are described.
Keywords :
matrix algebra; parameter estimation; low bias integrated path estimators; quadratic function; simulation output path; time-average variance constant; Analytical models; Computational modeling; Computer science; Convergence; Costs; Distributed computing; Parameter estimation; Reactive power; Steady-state; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Simulation Conference, 2007 Winter
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4244-1306-5
Electronic_ISBN :
978-1-4244-1306-5
Type :
conf
DOI :
10.1109/WSC.2007.4419616
Filename :
4419616
Link To Document :
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