Forecasting Performance of Arima and Sarima Models on Monthly Average Temperature of Zaria, Nigeria

Time series analysis and forecasting has become a major tool in different applications for research. Among the most effective approaches for analyzing time series data is the model introduced by Box and Jenkins. In this study, we used Box-Jenkins Methodology to find an appropriate Model among Autoregressive Integrated Moving Average (ARIMA) and Seasonal Autoregressive Integrated Moving Average (SARIMA) Model for temperature series of Zaria from 1993-2012. The data was tested for stationarity using ADF and KPSS. The best candidate Model from ARIMA and SARIMA were selected based on information criteria (AIC, AIC C and BIC) as well as diagnostic checking and forecasting accuracy measure. The Model that emerge best among the competing models is SARIMA (1,0,1)(0,1,1) 12 . Also the margin between the original series and the in sample forecast shows the reliability of the model estimated and this could be suitable for researchers in the field hydrology and meteorology.