Afrika Statistika

$K$-antithetic variates in Monte Carlo simulation

Abdelaziz Nasroallah

Full-text: Open access

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.

Article information

Source
Afr. Stat., Volume 3, Number 1 (2008), 144-155.

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

Permanent link to this document
https://projecteuclid.org/euclid.as/1495818318

Digital Object Identifier
doi:10.4314/afst.v3i1.46879

Mathematical Reviews number (MathSciNet)
MR2531126

Zentralblatt MATH identifier
1221.65013

Subjects
Primary: 65C05: Monte Carlo methods
Secondary: 65D30: Numerical integration

Citation

Nasroallah, Abdelaziz. $K$-antithetic variates in Monte Carlo simulation. Afr. Stat. 3 (2008), no. 1, 144--155. doi:10.4314/afst.v3i1.46879. https://projecteuclid.org/euclid.as/1495818318


Export citation