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

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

Management Science, 1992, vol. 38, issue 2, 170-181

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.

Keywords: supercomputers; distribution sampling; multivariate distribution; common seeds; metamodel (search for similar items in EconPapers)
Date: 1992
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:38:y:1992:i:2:p:170-181

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