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Titel A complex autoregressive model and application to monthly temperature forecasts
VerfasserIn X. Gu, J. Jiang
Medientyp Artikel
Sprache Englisch
ISSN 0992-7689
Digitales Dokument URL
Erschienen In: Annales Geophysicae ; 23, no. 10 ; Nr. 23, no. 10 (2005-11-30), S.3229-3235
Datensatznummer 250015395
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/angeo-23-3229-2005.pdf
 
Zusammenfassung
A complex autoregressive model was established based on the mathematic derivation of the least squares for the complex number domain which is referred to as the complex least squares. The model is different from the conventional way that the real number and the imaginary number are separately calculated. An application of this new model shows a better forecast than forecasts from other conventional statistical models, in predicting monthly temperature anomalies in July at 160 meteorological stations in mainland China. The conventional statistical models include an autoregressive model, where the real number and the imaginary number are separately disposed, an autoregressive model in the real number domain, and a persistence-forecast model.
 
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