Efficiency of Multivariate Control Variates in Monte Carlo Simulation
Reuven Y. Rubinstein and
Ruth Marcus
Additional contact information
Reuven Y. Rubinstein: Technion, Istrael Institute of Technology, Haifa, Israel
Ruth Marcus: Agricultural Research Organization, Beth-Dagan, Israel
Operations Research, 1985, vol. 33, issue 3, 661-677
Abstract:
This paper considers some statistical aspects of applying control variates to achieve variance reduction in the estimation of a vector of response variables in Monte Carlo simulation. It gives a result that quantifies the loss in variance reduction caused by the estimation of the optimal control matrix. For the one-dimensional case, we derive analytically the optimal size of the vector of control variates under specific assumptions on the covariance matrix. For the multidimensional case, our numerical results show that good variance reduction is achieved when the number of control variates is relatively small (approximately of the same order as the number of unknown parameters). Finally, we give some recommendations for future research.
Keywords: 767 control variates; 796 variance reduction (search for similar items in EconPapers)
Date: 1985
References: Add references at CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
http://dx.doi.org/10.1287/opre.33.3.661 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:33:y:1985:i:3:p:661-677
Access Statistics for this article
More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().