ISSN:
1436-3259
Keywords:
Contemporaneous ARMA models
;
maximum likelihood estimation
;
multivariate modelling
;
stochastic hydrology
;
time series analysis
Source:
Springer Online Journal Archives 1860-2000
Topics:
Architecture, Civil Engineering, Surveying
,
Energy, Environment Protection, Nuclear Power Engineering
,
Geography
,
Geosciences
Notes:
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.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF01543810
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