Comparison of Prediction Accuracy of Multiple Linear Regression, ARIMA and ARIMAX Model forPest Incidence of Cotton with Weather Factors
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Author:V.S. Aswathi and M.R. Duraisamy
Page No: 313-316
DOI:10.29321/MAJ.2018.000151
Abstract
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
