DocumentCode
2570586
Title
Confidence Intervals for Quantiles When Applying Latin Hypercube Sampling
Author
Nakayama, Marvin K.
Author_Institution
Comput. Sci. Dept., New Jersey Inst. of Technol., Newark, NJ, USA
fYear
2010
fDate
22-27 Aug. 2010
Firstpage
78
Lastpage
81
Abstract
Latin hypercube sampling (LHS) is a variance-reduction technique (VRT) that can be thought of as an extension of stratified sampling in higher dimensions. It can also be considered a generalization of antithetic variates, another VRT. This paper develops asymptotically valid confidence intervals for quantiles that are estimated via simulation using LHS.
Keywords
covariance analysis; sampling methods; Latin hypercube sampling; confidence intervals; quantiles; simulation; stratified sampling; variance-reduction technique; Analytical models; Estimation; Hypercubes; Monte Carlo methods; Portfolios; Random variables; Stochastic processes; Latin hypercube sampling; confidence interval; quantile; variance reduction;
fLanguage
English
Publisher
ieee
Conference_Titel
Advances in System Simulation (SIMUL), 2010 Second International Conference on
Conference_Location
Nice
Print_ISBN
978-1-4244-7783-8
Electronic_ISBN
978-0-7695-4142-6
Type
conf
DOI
10.1109/SIMUL.2010.10
Filename
5601893
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