Modeling and Forecasting of Armed Robbery Cases in Nigeria using Auto Regressive Integrated Moving Average (ARIMA) Models
We have utilized a twenty-nine year crime data in Nigeria pertaining to Armed Robbery, the study proposes crime modeling and forecasting using Autoregressive Integrated Moving Average Models, the best model were selected based on the minimum Akaike information criteria (AIC), Bayesian information cr...
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| Tipo de documento: | Electrónico Libro |
| Lenguaje: | Inglés |
| Publicado: |
2016
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| En: | Año: 2016 |
| Acceso en línea: |
Volltext (kostenfrei) |
| Verificar disponibilidad: | HBZ Gateway |
| Sumario: | We have utilized a twenty-nine year crime data in Nigeria pertaining to Armed Robbery, the study proposes crime modeling and forecasting using Autoregressive Integrated Moving Average Models, the best model were selected based on the minimum Akaike information criteria (AIC), Bayesian information criteria(BIC), and Hannan-Quinn criteria (HQC) values and was used to make forecast. Forecasted values suggest that Armed Robbery would slightly be on the increase Keywords: crime rate, ARIMA, armed robbery, forecasting, ACF/PACF, Akaike information criteria, Bayesian information criteria, Hannan-Quinn criteria |
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