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2008 $K$-antithetic variates in Monte Carlo simulation
Abdelaziz Nasroallah
Afr. Stat. 3(1): 144-155 (2008). DOI: 10.4314/afst.v3i1.46879

Abstract

Standard Monte Carlo simulation needs prohibitive time to achieve reasonable estimations. for untractable integrals (i.e. multidimensional integrals and/or intergals with complex integrand forms). Several statistical technique, called variance reduction methods, are used to reduce the simulation time. In this note, we propose a generalization of the well known antithetic variate method. Principally we propose a $K$−antithetic variate estimator (KAVE) based on the generation of $K$ correlated uniform variates. Some numerical examples are presented to show the improvenment of our proposition.

Citation

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Abdelaziz Nasroallah. "$K$-antithetic variates in Monte Carlo simulation." Afr. Stat. 3 (1) 144 - 155, 2008. https://doi.org/10.4314/afst.v3i1.46879

Information

Received: 27 December 2008; Revised: 16 January 2009; Published: 2008
First available in Project Euclid: 26 May 2017

zbMATH: 1221.65013
MathSciNet: MR2531126
Digital Object Identifier: 10.4314/afst.v3i1.46879

Subjects:
Primary: 65C05
Secondary: 65D30

Rights: Copyright © 2008 The Statistics and Probability African Society

Vol.3 • No. 1 • 2008
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