Computational Framework for Trend Pattern Analysis of Wheat Production in Some Wheat Growing States of India

The present study deals with the trend pattern analysis of wheat production in some wheat growing states of India on fitting well-known statistical models. The analysis was carried out on utilizing secondary time series data on wheat production. The trend values were obtained on fitting the statistical models, and the goodness of fit of the models was tested using chi-square test. Furthermore, statistical measures, viz. coefficient of determination (R2), root mean square error (RMSE), and relative mean absolute percentage error (RMAPE) were computed for revealing the model accuracy. The model with R2>0.5, and least values of RMSE and RMAPE, is regarded as the best model. Among the models considered under study, the cubic model was found to be the best in terms of precision for exploring the trends of wheat production in the concerned states. The findings of the study provide some useful insights on statistical modeling techniques for forecasting the scenario of wheat production in the concerned states.