Threshold modeling: application to air traffic flow at Muscat international airport

Linear models have drawn much attention due to their relative simplicity in understanding and implementation. However, many practical time series show non-linear patterns. Non- linear models are appropriate for predicting volatility changes time series. Various nonlinear models have been suggested in literature that includes threshold autoregressive (TAR). TAR models have been applied to predict stock price movements among many other applications. The overall objective of this study is to develop a threshold autoregressive (TAR) model and use it to predict the passenger flow at the Muscat International Airport.

Linear models have drawn much attention due to their relative simplicity in understanding and implementation. However, many practical time series show non-linear patterns. Non- linear models are appropriate for predicting volatility changes time series. Various nonlinear models have been suggested in literature that includes threshold autoregressive (TAR). TAR models have been applied to predict stock price movements among many other applications. The overall objective of this study is to develop a threshold autoregressive (TAR) model and use it to predict the passenger flow at the Muscat International Airport.