Variance reduction for Markov chain processes using state space evaluation for control variates

F A Dahl
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F A Dahl: Norwegian Defence Research Establishment

Journal of the Operational Research Society, 2001, vol. 52, issue 12, 1402-1407

Abstract: Abstract We develop a method for reducing variance in Monte Carlo simulation of Markov chain processes based on extracting accurate control variates from state space evaluation functions. An example is given in the form of a simple combat model, where the net variance reduction (adjusted for additional calculation) is larger than a factor of 80. We also indicate how our algorithm may be applied to discrete event simulations and system dynamic models with discrete random events.

Keywords: simulation; Markov chains; neural net training; variance reduction (search for similar items in EconPapers)
Date: 2001
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DOI: 10.1057/palgrave.jors.2601232

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