Cramer-von Mises Variance Estimators for Simulations

dc.contributor.author	Goldsman, David
dc.contributor.author	Kang, Keebom
dc.contributor.author	Seila, Andrew F.
dc.date.accessioned	2014-01-29T23:39:19Z
dc.date.available	2014-01-29T23:39:19Z
dc.date.issued	1991
dc.identifier.uri	https://hdl.handle.net/10945/38618
dc.description	Proceedings of the 1991 Winter Simulation Conference Barry L. Nelson, W. David Kelton, Gordon M. Clark (eds.)	en_US
dc.description.abstract	We study estimators for the variance parameter u 2 of a stationary process. The estimators are based on weighted Cramer-van Mises statistics formed from the standardized time series of the process. Certain weightings yield estimators which are "first-order unbiased" for u2 and which have low variance. We also show how the Cramer-von Mises estimators are related to the standardized time series area estimator; we use this relationship to establish additional estimators for u2 .	en_US
dc.rights	This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.	en_US
dc.title	Cramer-von Mises Variance Estimators for Simulations	en_US
dc.type	Conference Paper	en_US
dc.contributor.department	Department of Administrative Sciences

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