Modeling and Forecasting Sales Data by Time Series Analysis
用时间序列技术对销售数据建模，发现季节性可用确定性函数近似，随机部分为六阶自回归移动平均模型，组合模型用于最小均方预测，结果可靠。
Time series modeling technique is used to model a series of sales data in which seasonality causes distinct spike peaks. The analysis of actual sales data shows that the seasonality in the data can be approximated by a deterministic function and the stochastic component is a sixth-order autoregressive moving average model. Use of the combined deterministic and stochastic models to derive the minimum mean squared forecast yields reliable results.