Abstract
A computer simulation model is unusual in that the random error is under the total control of the experimenter. Variance reduction methods aim to take advantage of this to improve experimental accuracy. The fundamental ideas behind the most important of these methods are described and illustrated with simple examples.
Cite
CITATION STYLE
APA
Kloeden, P. E., & Platen, E. (1992). Variance Reduction Methods. In Numerical Solution of Stochastic Differential Equations (pp. 511–527). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-12616-5_16
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