Quantile estimation using a combination of stratified sampling and control variates

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

Abstract

Quantiles are used to measure risk in many application areas. We consider simulation methods for estimating a quantile using a variance-reduction technique that combines stratified sampling and control variates. We provide an asymptotically valid confidence interval for the quantile.

Original languageEnglish (US)
Title of host publicationIndustrial Engineering, Management Science and Applications 2015
EditorsKuinam J. Kim, Mitsuo Gen, Yabe Hiroshi, Xiaoxia Huang
PublisherSpringer Verlag
Pages105-114
Number of pages10
ISBN (Print)9783662471999
DOIs
StatePublished - 2015
EventInternational Conference on Industrial Engineering, Management Science and Applications, ICIMSA 2015 - Tokyo, Japan
Duration: May 26 2015May 28 2015

Publication series

NameLecture Notes in Electrical Engineering
Volume349
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Other

OtherInternational Conference on Industrial Engineering, Management Science and Applications, ICIMSA 2015
Country/TerritoryJapan
CityTokyo
Period5/26/155/28/15

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

Keywords

  • Confidence interval
  • Monte Carlo simulation
  • Quantile
  • Risk
  • Value-at-risk
  • Variance reduction

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