Variance Reduction of Quantile Estimates via Nonlinear Controls
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Authors
Lewis, Peter A.W.
Ressler, Richard L.
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1989
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Abstract
Linear controls are a well known techniques for achieving variance reduction in computer simulation. Unfortunately the effectiveness of a linear control depends upon the correlation between the statistic of interest and control which is often low. Since statistics are often nonlinear functions of the control this implies that nonlinear controls offer a means for improvement over linear controls. Nonlinear controls have had success in increasing the variance reduction over a linear control. This current work focuses on the use of nonlinear controls for reducing the variance of quantile estimates. The paper begins with a short discussion of linear controls. It describes nonlinear controls and the possibility for improved performance. The final sections discuss quantiles as controls and potential nonlinear controls for variance reduction in quantile estimation.
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Conference Paper
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Proceedings of the 1989 Winter Simulation Conference, E.A. MacNair, K.J. Musselman, P. Heidelberger (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.