DocumentCode :
2896651
Title :
Cramer-von Mises variance estimators for simulations
Author :
Goldsman, David ; Kang, Keebom ; Seila, Andrew F.
Author_Institution :
Sch. of Ind. & Syst. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fYear :
1991
fDate :
8-11 Dec 1991
Firstpage :
916
Lastpage :
920
Abstract :
The authors study estimators for the variance parameter σ 2 of a stationary process. The estimators are based on weighted Cramer-von Mises statistics formed from the standardized time series of the process. Certain weightings yield estimators which are first-order unbiased for σ2 and which have low variance. It is also shown how the Cramer-von Mises estimators are related to the standardized time series area estimator; this relationship is used to establish additional estimators for σ2
Keywords :
parameter estimation; simulation; time series; Cramer-von Mises variance estimators; simulations; standardized time series; stationary process; time series area estimator; variance parameter; weighted Cramer-von Mises statistics; Statistical distributions; Stochastic processes; Sufficient conditions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Simulation Conference, 1991. Proceedings., Winter
Conference_Location :
Phoenix, AZ
Print_ISBN :
0-7803-0181-1
Type :
conf
DOI :
10.1109/WSC.1991.185705
Filename :
185705
Link To Document :
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