Smarter Control Variables: Regression-Adjusted Linear and Nonlinear Controls

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Authors
Lewis, Peter A.W.
Ressler, Richard
Wood, R. Kevin
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1987
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Abstract
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.
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Conference Paper
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Proceedings of the 1987 Winter Simulation Conference, A. Thesen, H. Grant, W. David Kelton (eds.)
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This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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