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Multivariate contemporaneous ARMA model with hydrological applications
Authors:F Camacho  A I McLeod  K W Hipel
Institution:1. Dept. of Statistics and Actuarial Sciences, The University of Western Ontario, N6A 5B9, London, Ontario, Canada
2. Dept. of Systems Design Engineering and Dept. of Statistics and Actuarial Sciences, University of Waterloo, N2L 3G1, Ontario, Canada
Abstract:In order to allow contemporaneous autoregressive moving average (CARMA) models to be properly applied to hydrological time series, important statistical properties of the CARMA family of models are developed. For calibrating the model parameters, efficient joint estimation procedures are investigated and compared to a set of uivariate estimation procedures. It is shown that joint estimation procedures improve the efficiency of the autoregressive and moving average parameter estimates, but no improvements are expected on the estimation of the mean vector and the variance covariance matrix of the model. The effects of the different estimation procedures on the asymptotic prediction error are also considered. Finally, hydrological applications demonstrate the usefulness of the CARMA models in the field of water resources.
Keywords:
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