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Vector Computers, Monte Carlo Simulation and Regression Analysis: An Introduction

Author

Listed:
  • Jack P. C. Kleijnen

    (Department of Information Systems and Auditing, School of Business and Economics, Katholieke Universiteit Brabant (Tilburg University), 5000 LE Tilburg, The Netherlands)

  • Ben Annink

    (Department of Information Systems and Auditing, School of Business and Economics, Katholieke Universiteit Brabant (Tilburg University), 5000 LE Tilburg, The Netherlands)

Abstract

Vector computers provide a new tool for management scientists. The application of that tool requires thinking in vector mode. This mode is examined in the context of Monte Carlo experiments with regression models; these regression models may serve as metamodels in simulation experiments. The vector mode needs to exploit a specific dimension of the Monte Carlo experiment, namely the replicates of that experiment. Taking advantage of the machine architecture gives a code that computes Ordinary Least Squares estimates on a Cyber 205 in only 2% of the time needed on a Vax 8700. For Generalized Least Squares estimates, however, the code runs slower on the Cyber 205 than on the VAX, if the regression model is small; for large models the CYBER 205 runs much faster.

Suggested Citation

  • Jack P. C. Kleijnen & Ben Annink, 1992. "Vector Computers, Monte Carlo Simulation and Regression Analysis: An Introduction," Management Science, INFORMS, vol. 38(2), pages 170-181, February.
  • Handle: RePEc:inm:ormnsc:v:38:y:1992:i:2:p:170-181
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    File URL: http://dx.doi.org/10.1287/mnsc.38.2.170
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    Citations

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    Cited by:

    1. Bettonvil, B.W.M. & Kleijnen, J.P.C., 1991. "Identifying the important factors in simulation models with many factors," Research Memorandum FEW 498, Tilburg University, School of Economics and Management.
    2. Kleijnen, J.P.C. & Bettonvil, B.W.M., 1997. "Searching for important factors in simulation models with many factors : Sequential bifurcation," Other publications TiSEM be826993-22f9-4cb3-89df-3, Tilburg University, School of Economics and Management.
    3. Bettonvil, Bert & Kleijnen, Jack P. C., 1997. "Searching for important factors in simulation models with many factors: Sequential bifurcation," European Journal of Operational Research, Elsevier, vol. 96(1), pages 180-194, January.

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