需要予測における季節変動の統計的考察

Abstract

A demand forecast plays a very important role in modern management. The time series data analysis is one of the techniques used in demand forecasting. This analytical method consists of trend in movement, cyclical movement, seasonal movement and irregular component of demand. There have been several analytical methods available to deal with seasonal movement. The present study discusses statistical considerations on a seasonal distinction average method, link relatives method, moving average ratio method and sequential forecast method. The amounts sold by the department stores were used to show numerical examples. As the results of caliculations, obtained probabilities for the forecast error, observing the ±5% level of forecasting accuracy, are 0.606,0.648,0.653 and 0.627 respectively.