@inproceedings{364651e3680f4e69b38860750b7fadc4,

title = "Confidence intervals for quantiles when applying replicated latin hypercube sampling and sectioning",

abstract = "Latin hypercube sampling (LHS), which can be viewed as an extension of stratified sampling to multiple dimensions, is a variance-reduction technique that increases statistical efficiency by inducing correlation among the outputs. We use a method known as sectioning to develop confidence intervals for quantiles when applying replicated Latin hypercube sampling (rLHS). Both two-sided and one-sided confidence intervals are given, and the intervals are asymptotically valid. One application of the technique is for uncertainty and safety analyses of nuclear power plants.",

keywords = "Confidence interval, Latin hypercube sampling, Quantile, Sectioning",

author = "Marvin Nakayama",

year = "2012",

month = dec,

day = "1",

language = "English (US)",

isbn = "9781622761012",

series = "Simulation Series",

number = "16",

pages = "12--19",

booktitle = "Energy, Climate and Environment Modeling and Simulation 2012, ECEMS 2012 - 2012 Autumn Simulation Multiconference, AutumnSim 2012",

edition = "16",

note = "Energy, Climate and Environment Modeling and Simulation 2012, ECEMS 2012, Part of the 2012 Autumn Simulation Multiconference, AutumnSim 2012 ; Conference date: 28-10-2012 Through 31-10-2012",

}