Multivariate contemporaneous ARMA model with hydrological applications
In order to allow contemporaneous autoregressive moving average models (CARMA) 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 univariate 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.
contemporaneous autoregressive moving average models
scientific article; zbMATH DE number 4076794
scientific article