Smarter Control Variables: Regression-Adjusted Linear and Nonlinear Controls
Lewis, Peter A.W.
Wood, R. Kevin
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Nonlinear regression-adjusted control variables are investigated for improving variance reduction in statistical and system simulations. Simple control variables are transformed using linear and nonlinear transformations, and parameters of these transformations are selected using linear or nonlinear least squares regression. As an example, piecewise powertransformed variables are used in the estimation of the mean for the two variable Anderson-Darling goodness-of-fit statistic Wi. Substantial variance reduction over straightforward controls is obtained. These parametric transformations are compared against optimal, additive, nonparametric transformations from ACE and are shown to be nearly optimal.
Proceedings of the 1987 Winter Simulation Conference, A. Thesen, H. Grant, W. David Kelton (eds.)
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Lewis, Peter A.W.; Ressler, Richard L.; Wood, R. Kevin (Monterey, California: Naval Postgraduate School., 1988-08); NPS55-88-007Nonlinear regression-adjusted control variables are investigated for improving variance reduction in statistical and systems simulations. To this end, simple control variables are piecewise sectioned and then transformed ...
An investigation of nonlinear controls and regression-adjusted estimators for variance reduction in computer simulation. Ressler, Richard L. (Monterey, California. Naval Postgraduate School, 1991-03);This dissertation develops new techniques for variance reduction in computer simulation. It demonstrates that applying nonlinear transformations to control variables can increase their effectiveness over linear controls. ...
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