Exact Optimal Fixed Width Confidence Interval Estimation for the Mean

Vikas Deep, Achal Bassamboo, Sandeep Juneja, Assaf Zeevi

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


We consider a classical problem in simulation/statistics - given i.i.d. samples of a rv, the goal is to arrive at a confidence interval (CI) of a pre-specified width varepsilon, and with a coverage guarantee that the mean lies in the CI with probability at least 1-delta for pre-specified deltain(0,1). This problem has been well studied in an asymptotic regime as varepsilon shrinks to zero. The novelty of our analysis is the derivation of the lower bound on the number of samples required by any algorithm to construct a CI of varepsilon -width with the coverage guarantee for fixed varepsilon > 0 and delta, and construction of an algorithm that, under mild assumptions, matches the lower bound. For simplicity, we present our results for rv belonging to a single parameter exponential family, and illustrate its efficacy through a numerical study.

Original languageEnglish (US)
Title of host publicationProceedings of the 2022 Winter Simulation Conference, WSC 2022
EditorsB. Feng, G. Pedrielli, Y. Peng, S. Shashaani, E. Song, C.G. Corlu, L.H. Lee, E.P. Chew, T. Roeder, P. Lendermann
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages11
ISBN (Electronic)9798350309713
StatePublished - 2022
Event2022 Winter Simulation Conference, WSC 2022 - Guilin, China
Duration: Dec 11 2022Dec 14 2022

Publication series

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


Conference2022 Winter Simulation Conference, WSC 2022

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications


Dive into the research topics of 'Exact Optimal Fixed Width Confidence Interval Estimation for the Mean'. Together they form a unique fingerprint.

Cite this