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

摘要

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