Predicting Penang Road Accidents Influences: Time Series Regression Versus Structural Time Series

Noor Wahida Md Junus; Mohd Tahir Ismail  and Zainudin Arsad

doi:10.17485/ijst/2015/v8i30/84147

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Predicting Penang Road Accidents Influences: Time Series Regression Versus Structural Time Series

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2015/v8i30/84147

Year: 2015, Volume: 8, Issue: 30, Pages: 1-10

Original Article

Predicting Penang Road Accidents Influences: Time Series Regression Versus Structural Time Series

Noor Wahida Md Junus^1*, Mohd Tahir Ismail² and Zainudin Arsad²

¹ Department of Mathematics, Sultan Idris Education University, Tanjung Malim – 35900, Malaysia; [email protected]
² School of Mathematical Sciences, Universiti Sains Malaysia, Minden – 11800, Malaysia; [email protected], [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Road accidents become a major cause of death in recent years. The trends of road accidents keep increasing from year to year. Therefore, this paper will compare two time series methods that are time series regression and structural time series of modeling road accidents in Penang from year 2001 until 2013. There are eight explanatory variables used to model the monthly number of road accidents. In the structural time series, level component is allowed to vary over time, while seasonal components are fixed. Results show that both models have a different view in term of the relationship and the factor contributing to road accidents. However the advantage goes to structural time series method in fitting the best model.