Statistics
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Item ARIMA model and neural network: a comparative study of crime rate modelling(2015) James, T. O.; Suleiman, S.; Udomboso, C. G.; Babayemi, A. W.Crime rate is a serious issue that affects everyone in society. It affects the victims, perpetrators, their families the government and even reality of good governance. In this study forecasting of crime rate using autoregression integrated moving average (AR1MA) model was compared with feed forward neural networks. The J multi software was used for analysis of data gotten from State Police Headquarter in Kebbi State from January 2004 to December 2013 and the series was stationary at first difference and ARIMA (0, 1, 1) was obtained as the best model for the series. This was model by Neural Network using SPSS. In the training of the network, the samples were automatically partitioned in to 73.3% of training and 26.7% of testing. The computational result shows that Artificial Neural Network provides better model than ARIMA by having minimum error in the in-sample and out -of- sample in MAE, MSE, and RMSE with 3.84614, 2.00466 and 1.41586 respectively.Item Autoregressive distributed lags (ARDL) modelling of the impacts of climate change on rice production in Kebbi State(Professional Statisticians Society of Nigeria, 2018) James, T. O.; Babayemi, A. W.; Abdulmuahymin, A. S.; Udomboso, C. G.; Bello, M. L.Autoregress Distributed Lag (ARDL) is an econometric model that determines the long run a d short run association between the Serial (Stationary/ non-stationary as well as reparameterizing them to Error correction model (EMC). Rice cultivation and production is a major source of income for millions of households around the globe especially in Nigeria. It is also a major staple food, but Climate change poses great threat to the stability and sustainability of rice production for sufficient agricultural system, since most Nigeria consumes rice more than other foods and Kebbi state, is one of the major states contributing to the total rice output of the country. Climate change is the major challenge facing rice production. This study therefore, investigates the long-run and short run effect of factors affecting rice production in Kebbi State. 1000 simulations of data were obtained from the data collected between the period of 2005 to 2016 from the state Ministry of Agriculture. The result showed that rainfall has impact both in the long run and short run; 100% increase in rainfall, will tend to give 99.98% increase in rice production in the long-run. However, temperature tends to show insignificant impact on rice production. The result of this paper facilitate understanding for government and agriculturist in the linkages between climate change variables and rice production which can boost and increases the production of rice in Kebbi State.