Confidence intervals for quantiles when applying latin hypercube sampling

Marvin Nakayama

doi:10.1109/SIMUL.2010.10

Confidence intervals for quantiles when applying latin hypercube sampling

Marvin Nakayama

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English (US)
Title of host publication	Proceedings - 2nd International Conference on Advances in System Simulation, SIMUL 2010
Pages	78-81
Number of pages	4
DOIs	https://doi.org/10.1109/SIMUL.2010.10
State	Published - Dec 1 2010
Event	2nd International Conference on Advances in System Simulation, SIMUL 2010 - Nice, France Duration: Aug 22 2010 → Aug 27 2010

Other

Other	2nd International Conference on Advances in System Simulation, SIMUL 2010
Country/Territory	France
City	Nice
Period	8/22/10 → 8/27/10

All Science Journal Classification (ASJC) codes

Modeling and Simulation

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10.1109/SIMUL.2010.10

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title = "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 multiple dimensions. This paper develops asymptotically valid confidence intervals for quantiles that are estimated via simulation using LHS.",

author = "Marvin Nakayama",

year = "2010",

month = dec,

day = "1",

doi = "10.1109/SIMUL.2010.10",

language = "English (US)",

isbn = "9780769541426",

pages = "78--81",

booktitle = "Proceedings - 2nd International Conference on Advances in System Simulation, SIMUL 2010",

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AU - Nakayama, Marvin

PY - 2010/12/1

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N2 - 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.

AB - 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.

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U2 - 10.1109/SIMUL.2010.10

DO - 10.1109/SIMUL.2010.10

M3 - Conference contribution

AN - SCOPUS:78649413823

SN - 9780769541426

SP - 78

EP - 81

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

T2 - 2nd International Conference on Advances in System Simulation, SIMUL 2010

Y2 - 22 August 2010 through 27 August 2010

ER -

Confidence intervals for quantiles when applying latin hypercube sampling

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