a complex autoregressive model and application to monthly temperature forecasts

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ID: 244173
2005
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Résumé
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.
Clé de Référence
gu2005annalesa Utilisez cette clé pour citer automatiquement dans le manuscrit lors de l'utilisation de SciMatic Manuscript Manager ou Thesis Manager
Auteurs X. Gu, J. Jiang
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Revue journal of food measurement and characterization
Année 2005
DOI
10.5194/angeo-23-3229-2005
URL
https://www.ann-geophys.net/23/3229/2005/angeo-23-3229-2005.pdf
Mots-clés
cosmic physics sciencephysicsgeophysics

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