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A hybrid method for forecasting with an introduction of a day of the week index to the daily shipping data of sanitary materials

机译:一种混合的预测方法,在卫生材料的每日运输数据中引入了星期几指数

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Correct sales forecasting is inevitable in industries. In industries, how to improve forecasting accuracy such as sales, shipping is an important issue. There are many researches made on this. In this paper, we make estimation of ARMA model parameter and then estimate smoothing constants. Combining the trend removing method with this method, we aim to improve forecasting accuracy. Furthermore, "a day of the week index" is newly introduced for the daily data and the forecasting is executed to the manufacturer's data of sanitary materials. We have obtained good result. The effectiveness of this method should be examined in various cases.
机译:在行业中,正确的销售预测是不可避免的。在行业中,如何提高销售,运输等预测准确性是一个重要的问题。对此进行了许多研究。在本文中,我们估算ARMA模型参数,然后估算平滑常数。将趋势消除方法与这种方法相结合,我们旨在提高预测准确性。此外,为每日数据新引入了“星期几指数”,并且对卫生材料的制造商数据进行了预测。我们取得了良好的结果。该方法的有效性应在各种情况下进行检查。

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