伊利诺代写论文:时间预测法

2016-12-12 06:48

伊利诺代写论文:时间预测法

时间序列数据的预测方法有很多种。可以得出结论，从描述性的数据，这两个数据集都随着时间的推移，随着季节的因素。在这种情况下，这种方法可能是合适的。该方法产生准确的预测，在一种情况下可能是适当的，在另一种情况下产生准确的预测。因此，有必要尝试多种方法，然后选出最合适的方法。所以对这些数据集的方法可以是温特斯指数平滑法、分解法、自回归模型和ARIMA季节乘积。

伊利诺代写论文:时间预测法

There are many kinds of forecasting method for time series data. The conclusion can be drawn from the descriptive of data that these two data sets both change as time goes with the factor of seasons. In this situation, such method may be suitable. Sincea method that produces accurate forecasts in one case may not be appropriate and produce accurate forecasts in another case. So it is necessary to try many methods and then pick out the most suitable one. So the methods for these data sets can be the Winters Exponential Smoothing, Decomposition, Autoregressive models and seasonal ARIMA.

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