需要予測における季節変動の統計的考察(第3報)

Abstract

The time series data analysis is one of the techniques used for demand forecasting. This analytical method consists of four types of movements such as trend movement, cyclical movement, seasonal movement and irregular component of demand. There have been several analytical methods available for dealing with seasonal movement. The 2nd report discussed the dummy variable method by means of a quarter data of the year. The present study analyzes seasonal movement in a dummy variable method by means of monthly data and compares statistical consideration on the results of the 2nd report with those of the present study. The amount sold the department stores were used to show mumerical examples. As the results of analysis, the probability for the forecast error at the levels of the ±5%, ±10% and ±15% forecasting accuracy are 0.578,0.838 and 0.936,respectively. The probablies for the ferecast error are the smaller, compared with those of the 2nd report.