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Central Limit Theorem for a Randomized Quasi-Monte Carlo Estimator of a Smooth Function of Means

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

Abstract

Consider estimating a known smooth function (such as a ratio) of unknown means. Our paper accomplishes this by first estimating each mean via randomized quasi-Monte Carlo and then evaluating the function at the estimated means. We prove that the resulting plug-in estimator obeys a central limit theorem by first establishing a joint central limit theorem for a triangular array of estimators of the vector of means and then employing the delta method.

Original languageEnglish (US)
Title of host publication2025 Winter Simulation Conference, WSC 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages307-317
Number of pages11
ISBN (Electronic)9798331587260
DOIs
StatePublished - 2025
Externally publishedYes
Event2025 Winter Simulation Conference, WSC 2025 - Seattle, United States
Duration: Dec 7 2025Dec 10 2025

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736

Conference

Conference2025 Winter Simulation Conference, WSC 2025
Country/TerritoryUnited States
CitySeattle
Period12/7/2512/10/25

All Science Journal Classification (ASJC) codes

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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