Comparison of Prediction Accuracy of Multiple Linear Regression, ARIMA and ARIMAX Model forPest Incidence of Cotton with Weather Factors


                                Identifying suitable statistical model for predicting pest incidence have important role in pest management programmes. For this study weekly data of aphid, thrips, jassid and whitefly incidence of cotton at the TNAU region, Coimbatore and the weather factors influencing these pests incidence were used for model development. Rainfall, maximum temperature, minimum temperature, morning humidity, evening humidity were used as the independent variables and MLR, ARIMA, ARIMAX models built for each pests. Comparison of these three models was done and checked the model accuracy using root mean square error value. It was found that for all pests ARIMAX model posses lowest RMSE value compared to ARIMA and MLR. So ARIMAX model was selected as best fit model

Key words : Cotton pests, Multiple linear regression, ARIMA, ARIMAX, Weather factors