Comparing the Forecasting Performance of Seasonal Arima and Holt -Winters Methods of Births at a Tertiary Healthcare Facility in Ghana (original) (raw)

Introduction: Studies have shown periodic variations in the number of births using different mathematical models. A study conducted at the Korle-Bu teaching hospital obtained Seasonal Autoregressive Integrated Moving Average (SARIMA) model on a monthly number of birth for an 11-year data. However, this study did not compare the obtained model with other forecasting methods to determine the method that will best explain the data. This study sought to compare seasonal SARIMA model with Holt-Winters seasonal forecasting methods for an 11-year time series data on the number of births.. Methods: Data were analysed in R software (version 3.3.3). Holt-Winters and seasonal ARIMA forecasting methods were applied to the birth data. The errors of the out – of-sample forecast of these methods were compared and the one with the least error was considered the best forecasting method. Results The in-sample forecasting errors showed that SARIMA (2,1,1) x (1,01,) was the best among the other models....