Road accidents in Nigeria have always been in the increase. Efforts made by Federal Road Safety Commission (FRSC) in tackling the menace have not yielded much result. This paper aims to find a suitable time series model to forecast the future characteristics of the road accident data on Oyo-Ibadan express road. The data used for this paper was monthly data collected for a period of Eleven years between 2004-2014. In achieving this, the additive model approach was adopted in the analysis. It includes the estimation of trend, seasonal variation and random variation using moving average method. Autoregressive Moving average model were also fitted to the data and the best order was choosing using Akaike Information Criteria (AIC). The order = c (1, 1, 2), seasonal = c (1, 1, 2)) gives the best description of the data with minimum (AIC). A forecast based on the model obtained was made by the use of m-step predictor. The time plot plotted shows that the graphs maintain a constant movement from 2004-2008 but increases abnormally in 2010 and later drop again maintaining appreciable downward movement as the year progresses. Judging from the result, accidents and deaths are higher during the festive period months because of the various festivities lined up during this period, which involve much more traveling than usual.
| Published in | Science Journal of Applied Mathematics and Statistics (Volume 4, Issue 4) |
| DOI | 10.11648/j.sjams.20160404.11 |
| Page(s) | 119-128 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2016. Published by Science Publishing Group |
Autoregressive Moving Average, Akaike Information Criteria (AIC), Road Accident, Trend
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APA Style
Oyenuga Iyabode Favour, Ayoola Femi Joshua, Shittu Olanrewaju Ismail. (2016). Statistical Analysis of Pattern on Monthly Reported Road Accidents in Nigeria. Science Journal of Applied Mathematics and Statistics, 4(4), 119-128. https://doi.org/10.11648/j.sjams.20160404.11
ACS Style
Oyenuga Iyabode Favour; Ayoola Femi Joshua; Shittu Olanrewaju Ismail. Statistical Analysis of Pattern on Monthly Reported Road Accidents in Nigeria. Sci. J. Appl. Math. Stat. 2016, 4(4), 119-128. doi: 10.11648/j.sjams.20160404.11
AMA Style
Oyenuga Iyabode Favour, Ayoola Femi Joshua, Shittu Olanrewaju Ismail. Statistical Analysis of Pattern on Monthly Reported Road Accidents in Nigeria. Sci J Appl Math Stat. 2016;4(4):119-128. doi: 10.11648/j.sjams.20160404.11
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Download@article{10.11648/j.sjams.20160404.11,
author = {Oyenuga Iyabode Favour and Ayoola Femi Joshua and Shittu Olanrewaju Ismail},
title = {Statistical Analysis of Pattern on Monthly Reported Road Accidents in Nigeria},
journal = {Science Journal of Applied Mathematics and Statistics},
volume = {4},
number = {4},
pages = {119-128},
doi = {10.11648/j.sjams.20160404.11},
url = {https://doi.org/10.11648/j.sjams.20160404.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20160404.11},
abstract = {Road accidents in Nigeria have always been in the increase. Efforts made by Federal Road Safety Commission (FRSC) in tackling the menace have not yielded much result. This paper aims to find a suitable time series model to forecast the future characteristics of the road accident data on Oyo-Ibadan express road. The data used for this paper was monthly data collected for a period of Eleven years between 2004-2014. In achieving this, the additive model approach was adopted in the analysis. It includes the estimation of trend, seasonal variation and random variation using moving average method. Autoregressive Moving average model were also fitted to the data and the best order was choosing using Akaike Information Criteria (AIC). The order = c (1, 1, 2), seasonal = c (1, 1, 2)) gives the best description of the data with minimum (AIC). A forecast based on the model obtained was made by the use of m-step predictor. The time plot plotted shows that the graphs maintain a constant movement from 2004-2008 but increases abnormally in 2010 and later drop again maintaining appreciable downward movement as the year progresses. Judging from the result, accidents and deaths are higher during the festive period months because of the various festivities lined up during this period, which involve much more traveling than usual.},
year = {2016}
}
TY - JOUR T1 - Statistical Analysis of Pattern on Monthly Reported Road Accidents in Nigeria AU - Oyenuga Iyabode Favour AU - Ayoola Femi Joshua AU - Shittu Olanrewaju Ismail Y1 - 2016/06/28 PY - 2016 N1 - https://doi.org/10.11648/j.sjams.20160404.11 DO - 10.11648/j.sjams.20160404.11 T2 - Science Journal of Applied Mathematics and Statistics JF - Science Journal of Applied Mathematics and Statistics JO - Science Journal of Applied Mathematics and Statistics SP - 119 EP - 128 PB - Science Publishing Group SN - 2376-9513 UR - https://doi.org/10.11648/j.sjams.20160404.11 AB - Road accidents in Nigeria have always been in the increase. Efforts made by Federal Road Safety Commission (FRSC) in tackling the menace have not yielded much result. This paper aims to find a suitable time series model to forecast the future characteristics of the road accident data on Oyo-Ibadan express road. The data used for this paper was monthly data collected for a period of Eleven years between 2004-2014. In achieving this, the additive model approach was adopted in the analysis. It includes the estimation of trend, seasonal variation and random variation using moving average method. Autoregressive Moving average model were also fitted to the data and the best order was choosing using Akaike Information Criteria (AIC). The order = c (1, 1, 2), seasonal = c (1, 1, 2)) gives the best description of the data with minimum (AIC). A forecast based on the model obtained was made by the use of m-step predictor. The time plot plotted shows that the graphs maintain a constant movement from 2004-2008 but increases abnormally in 2010 and later drop again maintaining appreciable downward movement as the year progresses. Judging from the result, accidents and deaths are higher during the festive period months because of the various festivities lined up during this period, which involve much more traveling than usual. VL - 4 IS - 4 ER -
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