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                                       Details for article 12 of 17 found articles
 
 
  More efficient monte carlo methods obtained by using ranked set simulated samples
 
 
Title: More efficient monte carlo methods obtained by using ranked set simulated samples
Author: Samawi, Hani M.
Appeared in: Communications in statistics
Paging: Volume 28 (1999) nr. 3 pages 699-713
Year: 1999
Contents: Estimation of integrals by crude Monte Carlo methods, using uniform simulated sample (USS) required a large sample size to achieve high accuracy. Reduction in sample size is achieved using USS with the sophisticated Monte Carlo methods such as antithetic, importance or control variate sampling. In this paper, we show that the performance of these methods is substantially improved by using ranked simulated samples (RSIS) in place of USS. This results in a very large saving in of simulated sample size and hence in cost and time. We show that the modified methods using RSIS provide unbiased estimators for the integrals. Some characteristics and theoretical concepts of RSIS are given. A simulation study is conducted to compare the performance of the methods using RSIS to USS.
Publisher: Taylor & Francis
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 12 of 17 found articles
 
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