Generating An Autocorrelated Sequence Of Random Variates Without Distorting Their Distribution

Author

John R. Metzner, Missouri University of Science and Technology

Abstract

Using moving averages to introduce autocorrelation into a sequence of pseudorandom variables will most often distort the shape of the distribution. When the correlation coefficients are to be zero from some lag onward, it is possible to compensate for most of the distortion by starting with variates from another distribution. It is shown how to calculate the moving average coefficients and the parameters of the basic sequence so as to achieve the desired autocorrelation while retaining fidelity with the desired distribution to four moments. The moving average approach yields an internal generation method having quite modest storage requirements. © 1982.

Recommended Citation

J. R. Metzner, "Generating An Autocorrelated Sequence Of Random Variates Without Distorting Their Distribution," Mathematics and Computers in Simulation, vol. 24, no. 1, pp. 60 - 64, Elsevier, Jan 1982.

The definitive version is available at https://doi.org/10.1016/0378-4754(82)90051-9

Department(s)

Computer Science

International Standard Serial Number (ISSN)

0378-4754

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2023 Elsevier, All rights reserved.

Publication Date

01 Jan 1982