On the Approximation of Multiple Integrals Using Multivariate Ranked Simulated Sampling
Document Type
Article
Publication Date
5-2007
Publication Title
Applied Mathematics and Computation
DOI
10.1016/j.amc.2006.09.121
Abstract
The idea of using ranked simulated sampling approach (RSIS) to improve the well known Monte Carlo methods of integration, introduced by Samawi [H.M. Samawi, More efficient Monte Carlo methods obtained by using ranked set simulated samples, Commun. Stat. Simulat. 28 (3) (1999) 699–713], is extended to multivariate ranked simulated sampling approach (MVRSIS) for multiple integration problems. It is demonstrated that this approach provides unbiased estimators and improves the performance of some of the Monte Carlo methods of multiple integrals approximation. This, results in large saving in terms of cost and time needed to attain a certain level of accuracy. Two illustrations using simulation are used to compare the relative performance of this approach relative to multivariate uniform simulation.
Recommended Citation
Al-Saleh, Mohammad F., Hani M. Samawi.
2007.
"On the Approximation of Multiple Integrals Using Multivariate Ranked Simulated Sampling."
Applied Mathematics and Computation, 188 (1): 345-352.
doi: 10.1016/j.amc.2006.09.121
https://digitalcommons.georgiasouthern.edu/biostat-facpubs/156
