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Application of SARIMA model to forecasting monthly Diabetic patients at Al-Baha Region



SARIMA were used to modelling and forecasting monthlyDiabetic patients time series. The best SARIMA models were selected based on their autocorrelation function (ACF), partial autocorrelation function (PACF). The ACF of the residuals plot shows the randomness andhomogeneity of model residuals. The performance and validation of the SARIMA model premasters wereevaluated based on various statistical measures. We found that the best model that represented the data is SARIMA (1,1,1) (2,0,0)12. Finally, the results obtained can be applied to predict the futures trend of the Diabetic in Al-Baha Region KSA

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