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Article
More Efficient Approximation of Multiple Integration Using Steady State Ranked Simulated Sampling
Communication in Statistics: (Simulation and Computations)
  • Hani Samawi, Georgia Southern University
  • Robert L. Vogel, Georgia Southern University
Document Type
Article
Publication Date
1-1-2013
DOI
10.1080/03610918.2011.636856
Disciplines
Abstract
This article extends the concept of using the steady state ranked simulated sampling approach (SRSIS) by Al-Saleh and Samawi (2000) for improving Monte Carlo methods for single integration problem to multiple integration problems. We demonstrate that this approach provides unbiased estimators and substantially improves the performance of some Monte Carlo methods for bivariate integral approximations, which can be extended to multiple integrals’ approximations. This results in a significant reduction in costs and time required to attain a certain level of accuracy. In order to compare the performance of our method with the Samawi and Al-Saleh (2007) method, we use the same two illustrations for the bivariate case.
Citation Information
Hani Samawi and Robert L. Vogel. "More Efficient Approximation of Multiple Integration Using Steady State Ranked Simulated Sampling" Communication in Statistics: (Simulation and Computations) Vol. 42 Iss. 2 (2013) p. 370 - 381
Available at: http://works.bepress.com/robert_vogel/59/