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Cramer-Von Mises Variance Estimators for Simulations
NAVAL POSTGRADUATE SCHOOL MONTEREY CA DEPT OF ADMINISTRATIVE SCIENCES
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We study estimators for the variance parameter sigma2 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. Simulation, Stationary process, Variance estimation, Standardized time series, Cramer-von mises estimator.
APPROVED FOR PUBLIC RELEASE