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Table 5 The one-step and multistep forecasting accuracy of the ARIMA and XGBoost models

From: Time series analysis of hemorrhagic fever with renal syndrome in mainland China by using an XGBoost forecasting model

Model

Strategy

Index

ARIMA

XGBoost

One-step

Multistep

One-step

Multistep

Training set

Test set

Training set

Test set

Training set

Test set

Training set

Test set

ME

− 7.149

− 61.448

− 7.149

− 259.878

8.111

33.622

8.111

97.931

RMSE

181.977

249.276

181.977

302.781

166.311

178.547

166.311

223.187

MAE

108.160

185.367

108.160

259.878

113.219

132.055

113.219

173.403

MPE

− 0.937

− 6.575

− 0.937

− 30.121

− 2.403

2.383

− 2.403

6.348

MAPE

10.293

18.561

10.293

30.121

11.596

12.353

11.596

15.615

MASE

0.442

0.757

0.442

1.062

0.462

0.526

0.462

0.691

ACF1

0.016

− 0.169

0.016

− 0.159

0.424

− 0.232

0.424

− 0.047

Theil’s U

NA

0.375

NA

0.441

NA

0.273

NA

0.398