a complex autoregressive model and application to monthly temperature forecasts

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2005
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Abstract
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.
Reference Key
gu2005annalesa Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;X. Gu;J. Jiang
Journal journal of food measurement and characterization
Year 2005
DOI
10.5194/angeo-23-3229-2005
URL
https://www.ann-geophys.net/23/3229/2005/angeo-23-3229-2005.pdf
Keywords
cosmic physics sciencephysicsgeophysics

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