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Modelling Theft Criminal Offence in Kwara State Using ARIMA

Author

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  • AKINYEMI, Emmanuel K

    (Dept. of Statistics, Federal School of Statistics, Nigeria)

  • OGUNLEYE, Abiodun O

    (Dept. of Statistics, Federal School of Statistics, Nigeria)

  • GUNSOLA, Obaseye A

    (Dept. of Statistics, Federal School of Statistics, Nigeria)

  • Olaoye, Hakeem O

    (Dept. of Statistics, Federal School of Statistics, Nigeria)

Abstract

A time series modeling approach (Box-Jenkins’ ARIMA model) has been used in this study to forecast theft criminal offence in Kwara state. This study is centered on Time Series Analysis of Data on theft criminal Offences in Kwara State from 2006– 2015 which is restricted to only theft criminal offences in the state. The best model is the model with the least AIC Value which is SARIMA (0,1,1)(2,0,0)[12] having its AIC Value to be 898.98. The ACF of Residual showed that nearly all the spikes are within the line of boundary and the Ljung-Box statistics showed that all p-value points are above 0.05 thereby showing the accuracy of the model is good to forecast. The histogram showed that residual for the forecast which reveal that the error term for the forecast satisfies the assumption of normality, i.e. residual of the forecast is normally distributed. It was concluded that there is no residual autocorrelation i.e. there is evidence of non-zero autocorrelations in the forecast errors at lags 1 to 21. It recommend that Government is therefore advised to aside Security operatives engage Landlords, Household heads, market women, communities/street leaders and elders as an extended mediums of getting security information.

Suggested Citation

  • AKINYEMI, Emmanuel K & OGUNLEYE, Abiodun O & GUNSOLA, Obaseye A & Olaoye, Hakeem O, 2021. "Modelling Theft Criminal Offence in Kwara State Using ARIMA," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 8(4), pages 177-182, April.
    • Handle: RePEc:bjc:journl:v:8:y:2021:i:4:p:177-182
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    References listed on IDEAS

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    3. Commandeur, Jacques J.F. & Koopman, Siem Jan, 2007. "An Introduction to State Space Time Series Analysis," OUP Catalogue, Oxford University Press, number 9780199228874, Decembrie.
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