DocumentCode
2942279
Title
Overlapping batch statistics
Author
Schmeiser, Bruce W. ; Avramidis, Thanos N. ; Hashem, Sherif
Author_Institution
Sch. of Ind. Eng., Purdue Univ., West Lafayette, IN, USA
fYear
1990
fDate
9-12 Dec 1990
Firstpage
395
Lastpage
398
Abstract
The authors discuss the extension of batching algorithms from sample means to more general estimators. They provide assumptions sufficient for unbiasedness and convergence and provide computationally efficient algorithms for variances and quantiles. Although the definitions, discussion, and examples generalize to general batching estimators, the authors consider only the completely overlapping version
Keywords
convergence; discrete event simulation; mathematics computing; statistics; computationally efficient algorithms; convergence; general estimators; overlapping batch statistics; quantiles; sample means; stochastic simulation; unbiasedness; variances; Computational modeling; Convergence; Error analysis; Estimation error; Industrial engineering; Lapping; Measurement standards; Sampling methods; Statistics; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Simulation Conference, 1990. Proceedings., Winter
Conference_Location
New Orleans, LA
Print_ISBN
0-911801-72-3
Type
conf
DOI
10.1109/WSC.1990.129549
Filename
129549
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