5.2.2. Forecasting Error Analysis Using Statistical Theory. Figure 6 shows the forecasting errors for the four models, and the ARIMA error fluctuates greatly. The frequency diagram
and box plot for the forecasting errors are shown in Figure 7. Figure 7(a) shows that the errors are mostly in the interval 0 to 3.40%. A few errors are greater than 3.40% and less than 5.1%, and the maximum and second largest error intervals only include the ARIMA forecasting error. These data demonstrate that ARIMA is unsuitable for forecasting electricity consumption in theNSW.As shown in Figure 7(b), in addition to the ARIMA model, the other three quartiles
(the lower, median, and upper quartiles) calculated for the other threemodels have similar variations in the range length. The whiskers in the box plot indicate the primary range
for the data, in which the lowest data are 1.5 times the interquartile range of the lower quartile and the highest data are 1.5 times the interquartile range of the upper quartile (see
Figure 7(c)). The outliers, which are not included between the whiskers, are represented by red small circles.The GM, IAGM, and CSGM forecasting errors do not have outliers, while the number of outliers for the ARIMA reaches 5.