Confidence intervals for quantiles when applying latin hypercube sampling

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Latin hypercube sampling (LHS) is a variance-reduction technique (VRT) that can be thought of as an extension of stratified sampling in multiple dimensions. This paper develops asymptotically valid confidence intervals for quantiles that are estimated via simulation using LHS.

Original languageEnglish (US)
Title of host publicationProceedings - 2nd International Conference on Advances in System Simulation, SIMUL 2010
Pages78-81
Number of pages4
DOIs
StatePublished - 2010
Event2nd International Conference on Advances in System Simulation, SIMUL 2010 - Nice, France
Duration: Aug 22 2010Aug 27 2010

Publication series

NameProceedings - 2nd International Conference on Advances in System Simulation, SIMUL 2010

Other

Other2nd International Conference on Advances in System Simulation, SIMUL 2010
Country/TerritoryFrance
CityNice
Period8/22/108/27/10

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation

Keywords

  • Confidence interval
  • Latin hypercube sampling
  • Quantile
  • Variance reduction

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