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Non-negative time series models for dry river flow

Published online by Cambridge University Press:  14 July 2016

Jane L. Hutton
Jane L. Hutton*
Affiliation:
University of Liverpool
*
∗ Postal address: Department of Statistics and Computational Mathematics, University of Liverpool, P.O. Box 147, Liverpool L69 3BX, UK.
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Abstract

Non-negative time series which are first-order autoregressive with a mixed exponential innovation process are studied. Properties and approximate marginal distributions for such series are found. Modifications to include exact zeroes and to increase variability so that the time series is a more realistic model of rivers which are dry for part of the year are discussed.

Keywords

EXPONENTIAL AUTOREGRESSIVE MODELSTORAGE MODELSSTREAMFLOWEPHEMERAL STREAMS

Information

Type
Research Papers
Information
Journal of Applied Probability , Volume 27 , Issue 1 , March 1990, pp. 171 - 182
Copyright
Copyright © Applied Probability Trust 1990 

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