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On Modeling Murder Crimes in Nigeria

Author

Listed:
  • Obubu Maxwell*

    (Department of Statistics, Nnamdi Azikiwe University, Awka, Nigeria)

  • Ikediuwa Udoka Chinedu

    (Department of Statistics, Nnamdi Azikiwe University, Awka, Nigeria)

  • Anabike Charles Ifeanyi

    (Department of Statistics, Nnamdi Azikiwe University, Awka, Nigeria)

  • Nwokike Chukwudike C.

    (Department of Statistics, Abia State University, Nigeria)

Abstract

This paper examines the modelling and forecasting Murder crimes using Auto-Regressive Integrated Moving Average models (ARIMA). Twenty-nine years data obtained from Nigeria Information Resource Center were used to make predictions. Among the most effective approaches for analyzing time series data is the method propounded by Box and Jenkins, the Autoregressive Integrated Moving Average (ARIMA). The augmented Dickey-Fuller test for unit root was applied to the data set to investigate for Stationarity, the data set was found to be non-stationary hence transformed using first-order differencing to make them Stationary. The Stationarities were confirmed with time series plots. Statistical analysis was performed using GRETL software package from which, ARIMA (0, 1, 0) was found to be the best and adequate model for Murder crimes. Forecasted values suggest that Murder would slightly be on the increase.

Suggested Citation

  • Obubu Maxwell* & Ikediuwa Udoka Chinedu & Anabike Charles Ifeanyi & Nwokike Chukwudike C., 2019. "On Modeling Murder Crimes in Nigeria," Scientific Review, Academic Research Publishing Group, vol. 5(8), pages 157-162, 08-2019.
    • Handle: RePEc:arp:srarsr:2019:p:157-162
    DOI: 10.32861/sr.58.157.162
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    References listed on IDEAS

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    1. Gorr, Wilpen & Olligschlaeger, Andreas & Thompson, Yvonne, 2003. "Short-term forecasting of crime," International Journal of Forecasting, Elsevier, vol. 19(4), pages 579-594.
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