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

Author

Takeyasu, Daisuke ; Yamashita, Hirotake ; Takeyasu, Kazuhiro

Author_Institution

Grad. Sch. of Culture & Sci., Open Univ. of Japan, Chiba, Japan

fYear

2014

Firstpage

1268

Lastpage

1273

Abstract

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.

Keywords

autoregressive moving average processes; economic forecasting; ARMA model parameter; correct sales forecasting; daily shipping data; forecasting accuracy improvement; hybrid method; sanitary materials; smoothing constants; trend removing method; week index; Autoregressive processes; Equations; Forecasting; Indexes; Market research; Mathematical model; Smoothing methods; Exponential Smoothing Method; Forecasting; Minimum Variance; Sanitary Materials; Trend;

fLanguage

English

Publisher

ieee

Conference_Titel

Soft Computing and Intelligent Systems (SCIS), 2014 Joint 7th International Conference on and Advanced Intelligent Systems (ISIS), 15th International Symposium on

Type

conf

DOI

10.1109/SCIS-ISIS.2014.7044509

Filename

7044509