Tag Archives: Airline Disasters

Autoregressive Integrated Moving Average (Arima) Model for the Major Airline Disasters in the World from 1960 Through 2013 (Published)

This research fit a univariate time series model to the major Airline Disasters in the world from 1960 through 2013. The Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) model was estimated and the best fitting ARIMA model was used to obtain the post-sample forecasts for five years. The fitted model was ARIMA (0,1,1) with Akaike Information Criteria (AIC) of 323.14, Normalized Bayesian Information Criteria (BIC) of 327.04, Stationary R2 of 0.348.This model was further validated by Ljung-Box test with no significant Autocorrelation between the residuals at different lag times and subsequently by white noise of residuals from the diagnostic checks performed which clearly portray randomness of the standard error of the residuals, no significant spike in the residual plots of ACF and PACF. The forecasts value indicates that Airline Disasters will increase slightly with almost equal number of cases for the next five years (2014-2018).

Keywords: ARIMA, Airline Disasters, Box- Jenkins, Forecast, Ljung-Box, Stationarity, Time Series, Unit Root