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Table 2 Deming regression for comparing GMDH-type ANN, ARIMA and Holt-Winters models

From: Time series prediction of under-five mortality rates for Nigeria: comparative analysis of artificial neural networks, Holt-Winters exponential smoothing and autoregressive integrated moving average models

Reference: Observed historical U5MR Proportional difference (slope) Systematic difference (intercept)
β1 (SE) 95% LCL, UCL P-value β0(SE) 95% LCL, UCL P-value
GMDH-type ANN 1.000 (0.0004) 0.999, 1.001 < 0.001 0.004 (0.058) −0.113, 0.122 0.940
ARIMA 1.000 (0.001) 0.998, 1.002 < 0.001 0.027 (0.160) −0.293, 0.348 0.865
Holt-Winters 1.000 (0.013) 0.969, 1.023 < 0.001 0.890 (2.349) −3.822, 5.602 0.706
  1. LCL Lower Confidence Limit, UCL Upper Confidence Limit, SE Jack-knife standard errors