-p_nn_exo = computeForecast(data, ${list_indices[i]}, "Neighbors", "Neighbors",
- horizon=H, simtype="exo")
-p_nn_mix = computeForecast(data, ${list_indices[i]}, "Neighbors", "Neighbors",
- horizon=H, simtype="mix")
-p_az = computeForecast(data, ${list_indices[i]}, "Average", "Zero",
- horizon=H)
-p_pz = computeForecast(data, ${list_indices[i]}, "Persistence", "Zero",
- horizon=${H}, same_day=${'TRUE' if loop.index < 2 else 'FALSE'})
+p_nn = computeForecast(data, ${list_indices[i]}, "Neighbors", "Neighbors", horizon=H)
+p_nn2 = computeForecast(data, ${list_indices[i]}, "Neighbors2", "Zero", horizon=H)
+p_az = computeForecast(data, ${list_indices[i]}, "Average", "Zero", horizon=H)
+p_pz = computeForecast(data, ${list_indices[i]}, "Persistence", "Zero", horizon=H, same_day=${'TRUE' if loop.index < 2 else 'FALSE'})