Cramer-Von Mises Variance Estimators for Simulations
Seila, Andrew F.
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We study estimators for the variance parameter sigma(2) of a stationary process. The estimators are based on weightings yield estimators that are 'first-order unbiased' for sigma (2) We derive an expression for the asymptotic variance of the new estimators; this expression is then used to obtain the first-order unbiased estimator having the smallest variance among fixed-degree polynomial weighting functions. Although our work is based on asymptotic theory, we present exact and empirical examples to demonstrate the new estimators' small-sample robustness.
RightsThis 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.
NPS Report NumberNPS-AS-93-028
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