Research on Time Series Analysis for Long Memory Process of Air Traffic Using ARFIMA

In the present study, the time series models ARIMA and ARFIMA or FARIMA models have been fitted to Air
India domestic air passengers, which considered as self similarity and Long Range Dependence (LRD). In such
case ARFIMA model is expected to be superior to ARIMA. We fitted ARIMA and ARFIMA models to air
traffic data and compared. Then the best model has been identified using RMSE, MAE and MAPE values. This
model can be useful to analyze the air traffic flow and revise the services of Air India. The analysis was carried
out using time series data on number of passengers travelling by Air India domestic flights during January 2012
to December 2018.