Rate the Article: Time Series Analysis of Road Accidents Using Autoregressive Integrated Moving Average (ARIMA) Model, IJSR, Call for Papers, Online Journal
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064

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Research Paper | Mathematics | Kenya | Volume 8 Issue 4, April 2019 | Rating: 6.7 / 10


Time Series Analysis of Road Accidents Using Autoregressive Integrated Moving Average (ARIMA) Model

Joel Cheruiyot Chelule, Meshack Kipchumba Ngetich, Ayubu Anapapa, Herbert Imboga


Abstract: The road transport industry in Kenya plays a vital role in the life of the majority of her citizens. Many Kenyans utilize different transport modes to reach their various destinations daily. Nearly 3000 people killed on Kenyan roads per year. The objective of this study was a time series analysis of road accidents trend in Kenya using the Autoregressive Integrated Model (ARIMA) model. This study used time series techniques which can better describe and model the accident data. This is achieved using suitable techniques whose performances are subsequently analyzed. The study utilized accident data between the years 2014-2017 obtained from National Transport Safety Authority. In this research project, the time series with Box Jenkins method applied to 4 years of annual road accident data from 2014 2017 to determine the trend of road traffic accident cases and deaths in Kenya. ARIMA models subsequently fitted for accident cases and deaths.


Keywords: Time Series Analysis, Road Accidents, Autoregressive Integrated Moving Average model ARIMA


Edition: Volume 8 Issue 4, April 2019,


Pages: 1747 - 1755



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