AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) APPROACH FOR PREDICTION OF RICE (ORYZA SATIVA L.) YIELD

In the present paper, different Autoregressive Integrated Moving Average (ARIMA) models were developed to forecast the rice yield by using time series data of sixty two years. The performance of these developed models were assessed with the help of different selection measure criteria and the model having minimum value of these criteria considered as the best forecasting model. Based on findings, it has been observed that out of eleven ARIMA models, ARIMA (1, 1, 1) is the best fitted model in predicting efficiently the rice yield as compared to others.