Table 5

Forecast accuracy for the 7 series' level and log-transformed test samples under four-step forecast

Forecast method 1 – ARIMA for test sample of level series at four-step forecast
Accuracy measureRoutes
SEAFI composite ARIMA(1,1,0)Singapore ARIMA(1,0,3)Vietnam ARIMA(0,1,4)Thailand ARIMA(1,1,0)The Philippines ARIMA(0,1,2)Malaysia ARIMA(1,1,0)Indonesia ARIMA(3,1,2)Average
RMSE234.04231.273128.08252.16931.67548.02063.29784.080
MAPE22.05715.03036.54026.66241.05017.32814.18424.693
Forecast method 2 – SNNAR for test sample of level series at four-step forecast
Accuracy measureRoutes
SEAFI composite SNNAR(2,1,2)Singapore SNNAR(2,1,2)Vietnam SNNAR(2,1,2)Thailand SNNAR(2,1,2)The Philippines SNNAR(7,1,4)Malaysia SNNAR(2,1,2)Indonesia SNNAR(2,1,2)Average
RMSE267.29334.77992.50845.40654.65053.20279.63989.639
MAPE27.26317.11328.35423.63556.68419.24921.71527.716
Forecast method 1 – ARIMA for test sample of log-transformed series at four-step forecast
Accuracy measureRoutes
SEAFI composite ARIMA(0,1,3)Singapore ARIMA(5,0,0)Vietnam ARIMA(1,1,0)Thailand ARIMA(1,1,0)The Philippines ARIMA(0,1,2)Malaysia ARIMA(1,1,0)Indonesia ARIMA(3,1,2)Average
RMSE0.320.2560.4960.3263.1680.2780.2440.727
MAPE3.7644.0367.6695.56336.1743.8812.9959.155
Forecast method 2 – SNNAR for test sample of log-transformed series at four-step forecast
Accuracy measureRoutes
SEAFI composite SNNAR(2,1,2)Singapore SNNAR (1,1,2)Vietnam SNNAR (2,1,2)Thailand SNNAR (2,1,2)The Philippines SNNAR(7,1,4)Malaysia SNNAR(2,1,2)Indonesia SNNAR(2,1,2)Average
RMSE0.460.2620.4170.3753.7250.3540.3030.842
MAPE5.6743.8246.3016.19242.4074.8784.46110.534

Source(s): Authors’ work

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