Forecasting Traffic Accidents According to (Types of Roads and their Causatives) in Iraq using ARMA of Low Ordered Combinations Models - Hafidh Jawad Al-Saadi, Nahla; ., . (International Journal of Engineering and Technology, 2018)
Objective: This research aimed to forecasting of an expected outcomes based on the numbers of traffic accidents concerning (Types of Roads, and Their Causatives), in Iraq through applying ARMA of low ordered combinations models.Methodology: Data are selected from annuls statistical reports traffic accidents registered and published by ministry of planning for the time periods (2002-2015). Two statistical criteria had been applied, such that (MSE, and MPE), first statistic measuring the magnitude of the errors, a better model will give a smaller value. The second statistic measuring the bias, a better model will give a value close to zero. As well as 95% confidence interval limits of predicating long term trend are estimated.Results and Findings: The best reference of predicating traffic accidents according to types of roads, and having significant parameters estimates in at least at P
Keywords: Traffic Accidents; Forecasting Methods; ARMA (p; q) Time Series Models; Goodness of Fit; Future Projection.