Cramer-von Mises Variance Estimators for Simulations
Seila, Andrew F.
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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 .
Proceedings of the 1991 Winter Simulation Conference Barry L. Nelson, W. David Kelton, Gordon M. Clark (eds.)
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A simulation study of estimates of a first passage time distribution for a censored semi-Markov process. Gallagher, Rick M. (1986-09);This thesis reports on a simulation study of parametric and nonparametric estimators of a first passage time distribution for a censored semi-Markov process. Four estimators are proposed and compared; Maximum Likelihood ...
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Seila, Andrew F.; Goldsman, David; Kang, Keebom (Monterey, California. Naval Postgraduate School, 1993-09); NPS-AS-93-028We 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 ...