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Optimal Estimator for Sample Size Using Monte-Carlo Method


Article Information

Title: Optimal Estimator for Sample Size Using Monte-Carlo Method

Authors: H. Bevrani, M. Ghorbani, M.K. Sadaghiani

Journal: Journal of Applied Sciences

HEC Recognition History
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Publisher: Asian Network for Scientific Information (ANSInet)

Country: Pakistan

Year: 2008

Volume: 8

Issue: 6

Language: English

DOI: 10.3923/jas.2008.1122.1124

Keywords: Monte-Carlo methodChebyshev`s inequalityBerry-Esseen`s inequality

Categories

Abstract

In this study, we construct the optimal estimator for sample size, which were sufficient for maintenance the demanded accuracy and reliability. The goal of this paper is presenting three estimators such as follow. The first one which is traditional approach and rough enough is based on the Chebyshev`s inequality. The second one is based on the central limit theorem, but it doesn`t take into account the accuracy of the normal approximation. The third estimator is based on Berry-Esseen`s inequality that takes into account the accuracy of the normal approximation and is guaranteed.


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