Nonlinear growth model in agriculture-A Review

To develop appropriate nonlinear statistical models with a view to provide analytical approach to describe the agricultural production trends in India. Reviews were made to study the various nonlinear statistical growth models. The parameters of each model were estimated using Levenberg -Marquardt (LM) iterative method. The main assumptions of ‘independence’ and ‘normality’ of error terms were examined by using the ‘Run-test’ and ‘Shapiro-Wilk test’ respectively. Measure the accuracy of the model fitting, we considered the performance of several model goodness of fit criteria viz., R2, MAE, MSE, RMSE, MAPE, AIC and BIC. Nonlinear model discussed important five points of consideration 1. Parsimony, 2. Parameterization, 3. Range of applicability, 4. Stochastic specification and 5. Interpretability.