Confidence Intervals for Quantiles When Applying Latin Hypercube Sampling

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.