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The forecasting performances of the MLR and WMLR models in terms of the MAE, RMSE, and [D.sub.stat] testing phase are compared and shown in Table 2.
For further analysis, the best performance of the LR, WMLR, ARIMA, and ARIMA-GARCH models was compared with the best results of ARIMA and forward neural network (FNN) studied by Yu et al.
Figure 5 shows the Box-plot for the ARIMA, ARIMAGARCH, MLR, and WMLR models for testing period.
The accuracy of the wavelet multiple linear regression (WMLR) technique in the forecasting daily crude oil has been investigated in this study.
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