Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-27T21:51:18.559Z Has data issue: false hasContentIssue false

Extending the correlation structure of exponential autoregressive–moving-average processes

Published online by Cambridge University Press:  14 July 2016

Ed McKenzie*
Affiliation:
University of Strathclyde
*
Postal address: Department of Mathematics, University of Strathclyde, Livingstone Tower, 26 Richmond St. Glasgow Gl 1XH, U.K.

Abstract

Some recent constructions for the generation of dependent sequences of identically distributed negative exponential random variables with specific correlation structures are generalized. This is achieved by attributing a correlation structure to the binary sequence which controls the generation of the exponentials. The procedure causes the autocorrelation function of the exponential sequence to copy that of the binary sequence and thus be extended to include negative values and other values beyond the usual range.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Jacobs, P. A. and Lewis, P. A. W. (1977) A mixed autoregressive—moving-average exponential sequence and point process (EARMA 1,1). Adv. Appl. Prob. 9, 87104.Google Scholar
Jacobs, P. A. and Lewis, P. A. W. (1978) Discrete time series generated by mixtures. I. Correlational and runs properties. J. R. Statist. Soc. B 40, 94105.Google Scholar
Kanter, M. (1975) Autoregression for discrete processes mod 2. J. Appl. Prob. 12, 371375.Google Scholar
Lawrance, A. J. and Lewis, P. A. W. (1977) An exponential moving-average sequence and point process (EMA 1). J. Appl. Prob. 14, 98113.Google Scholar
Moran, P. A. P. (1967) Testing for correlation between non-negative variates. Biometrika 54, 385394.Google Scholar