The second chart is the bar chart of the residuals.I wrote a little Python helper to help with this problem (see here). If only one quantitative explanatory variable has been selected, the first chart represents the data and the curve for the chosen function. Charts for nonlinear regression in XLSTAT It is followed by the equation of the model. Predictions and residuals: This table gives for each observation the input data, the value predicted by the model and the residuals. For built-in functions, or user-defined functions when derivatives for the parameters have been entered, the standard deviations of the estimators are calculated. Model parameters: This table gives the value of each parameter after fitting to the model.
When the derivatives are not available, a more complex and slower but efficient algorithm is used. When this is possible (preprogrammed functions or user-defined functions where the first derivatives have been entered by the user) the Levenberg-Marquardt algorithm is used. To improve the speed and reliability of the calculations, it is recommended to add derivatives of the function for each of the parameters of the model. When the model required is not available, the user can define a new model and add it to their personal library. Options for nonlinear regression in XLSTAT Adding a function to the library of user-defined functions The user is also free to write other nonlinear functions. XLSTAT provides preprogrammed functions from which the user may be able to select the model which describes the phenomenon to be modeled. Nonlinear regression is used to model complex phenomena which cannot be handled by the linear model.