Prediction of time series by the method of analogs |
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Authors: | E F Vasechkina V D Yarin |
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Institution: | (1) Marine Hydrophysical Institute, Ukrainian Academy of Sciences, Sevastopol |
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Abstract: | We consider an algorithm of prediction of nonstationary time series based on the method of analogs. Since the exhaustion of
a great number of versions is required for the adjustment of the parameters of the optimal prognostic model, we describe a
genetic algorithm used in this case. We consider several procedures of construction of prognostic models. The numerical results
are used to choose the procedure guaranteeing the minimum mean square error. The parameters of the model affecting the quality
of predictions are determined. The proposed method is tested by using the reanalysis data (NCEP/NCAR project) on the anomalies of the monthly average surface air temperature for 58 yr. The results of predictions are compared
with the estimates obtained by the linear regression method. It is shown that the method of analogs gives satisfactory results
even in the cases where the regression methods lead to errors equal to the variance of predicted series.
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Translated from Morskoi Gidrofizicheskii Zhurnal, No. 4, pp. 70–80, July–August, 2007. |
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