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A Weighted Least Squares Approach to Computer Simulation Factor Screening

Author

Listed:
  • Douglas J. Morrice
  • Indranil R. Bardhan

    (University of Texas at Austin, Austin, Texas)

Abstract

In this paper, we develop a weighted least squares (WLS) approach to computer simulation factor screening. Like frequency domain methodology (FDM), the regression analysis is performed in the frequency domain. However, unlike FDM, where unknown nuisance parameters are eliminated by cancellation in a ratio statistic, the WLS procedure is designed to estimate these parameters (the WLS weights) and incorporate this information into the regression analysis. We propose and compare one- and two-run approaches for estimating the weights in the WLS approach.

Suggested Citation

  • Douglas J. Morrice & Indranil R. Bardhan, 1995. "A Weighted Least Squares Approach to Computer Simulation Factor Screening," Operations Research, INFORMS, vol. 43(5), pages 792-806, October.
    • Handle: RePEc:inm:oropre:v:43:y:1995:i:5:p:792-806
    DOI: 10.1287/opre.43.5.792
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    Citations

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    Cited by:

    1. Kleijnen, J.P.C. & Sanchez, S.M. & Lucas, T.W. & Cioppa, T.M., 2003. "A User's Guide to the Brave New World of Designing Simulation Experiments," Other publications TiSEM a6910d11-f9bc-4246-b1a7-2, Tilburg University, School of Economics and Management.
    2. Indranil Bardhan & Jeong-ha (Cath) Oh & Zhiqiang (Eric) Zheng & Kirk Kirksey, 2015. "Predictive Analytics for Readmission of Patients with Congestive Heart Failure," Information Systems Research, INFORMS, vol. 26(1), pages 19-39, March.
    3. Shen, Hua & Wan, Hong, 2009. "Controlled sequential factorial design for simulation factor screening," European Journal of Operational Research, Elsevier, vol. 198(2), pages 511-519, October.
    4. Arsham H., 1998. "Techniques for Monte Carlo Optimizing," Monte Carlo Methods and Applications, De Gruyter, vol. 4(3), pages 181-230, December.
    5. Arsham Hossein, 2007. "Monte Carlo Techniques for Parametric Finite Multidimensional Integral Equations," Monte Carlo Methods and Applications, De Gruyter, vol. 13(3), pages 173-195, August.
    6. Jack P. C. Kleijnen & Susan M. Sanchez & Thomas W. Lucas & Thomas M. Cioppa, 2005. "State-of-the-Art Review: A User’s Guide to the Brave New World of Designing Simulation Experiments," INFORMS Journal on Computing, INFORMS, vol. 17(3), pages 263-289, August.
    7. Hong Wan & Bruce E. Ankenman & Barry L. Nelson, 2006. "Controlled Sequential Bifurcation: A New Factor-Screening Method for Discrete-Event Simulation," Operations Research, INFORMS, vol. 54(4), pages 743-755, August.

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