Technical Note—Bootstrap-based Budget Allocation for Nested Simulation

Kun Zhang (), Guangwu Liu () and Shiyu Wang ()
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Kun Zhang: Institute of Statistics and Big Data, Renmin University of China, Beijing 100872, China
Guangwu Liu: Department of Management Sciences, College of Business, City University of Hong Kong, Kowloon, Hong Kong, China
Shiyu Wang: Department of Management Sciences, College of Business, City University of Hong Kong, Kowloon, Hong Kong, China

Operations Research, 2022, vol. 70, issue 2, 1128-1142

Abstract: Simulation budget allocation is at the heart of a nested (also referred to as two-level) simulation approach to estimating functionals of a conditional expectation. In this paper, we propose a sample-driven budget allocation rule under a unified nested simulation framework that allows for different forms of functionals. The proposed method employs bootstrap sampling to guide an effective choice of outer- and inner-level sample sizes. Furthermore, we establish a central limit theorem for nested simulation estimators, and incorporate the sample-driven allocation rule into the construction of asymptotically valid confidence intervals (CIs). Effectiveness of the sample-driven allocation rule and validity of the constructed CIs are confirmed by numerical experiments.

Keywords: Simulation; nested simulation; budget allocation; bootstrap sampling; confidence intervals (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:70:y:2022:i:2:p:1128-1142

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