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Empirical Analysis of Smoothing the Abnormal Fluctuant Statistical Data

Guangrong Tong, Yucheng Liu

Abstract



The statistical data is usually influenced by all kinds of abnormal fluctuant factors. By measuring these factors, we can separate them from the statistical data or offset them by the smooth processing technology and therefore get adjusted statistical data which can reflect the real economical trend. Based on China’s statistical data, the paper studies the smooth processing methods of the abnormal fluctuant data and presents the smoothing models. For the data of overall index, the differencial exponential smoothing method of order one is suitable. And for the data of relative index, firstly adjusting the data by the vector autoregressive model (VAR) and the vector error correction model (VEC) and then smoothing the adjusted data by the double exponential smoothing method is suitable. The simulation results show that our smooth processing method is appropriate for the abnormal fluctuant data.



Keywords


abnormal fluctuation, smooth processing, exponential smoothing, VAR model, VEC model.

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