Abstract
Present study deals with different linear and non-linear statistical models like multiple linear regression (MLR) model, autoregressive integrated moving average (ARIMA) model and artificial neural network (ANN) for forecastingpigeon pea yield grown in Varanasi region of Uttar Pradesh using 27 years of data (1985-86 to 2011-12). The performance of the model was assessed by root mean squared error (RMSE). On the basis of empirical studies, ANN was found to be best suitable model having lowest RMSE with forecasted yield during the year 2012-13 for Varanasi region.
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