analyzing the amount of hemoglobin a1c using singular spectrum analysis

Monthly hemoglobin a1c levels are a proper estimator in patients withdiabetes type ii for adequate diabetes control. in this paper, we apply singular spectrumanalysis (ssa), which is a non-parametric powerful method for forecasting and timeseries analysis, to forecast the amount of hemoglobin a1c. the results of two forecastingapproaches in the ssa, namely vector and recurrent forecasting, are compared to thosefrom other techniques including arima, arfima, bats, tbats, and ets. thecomparison is made using the two accuracy measures root mean squared error (rmse)and mean absolute error (mae).