The initial Nonlinear Fit report includes the following items, shown in Initial Nonlinear Fit Report.

Go starts the fitting process.

Stop stops the fitting process.

Step proceeds through the fitting process one iteration at a time.

Reset reset the editable values into the formula, reset the iteration values, and calculate the SSE at these new values.

Criterion shows iteration measures from the fitting process and the Current values.

Stop Limit sets limits on the Criterion.

Shows a plot of the X and Y variables for models with only one X variable. The model based on the current values is shown on the plot. To change the current values of the parameters, use the sliders or edit boxes beneath the plot.

After you click Go to fit a model, the report includes the following additional items, shown in Fitted Model Report.

Computes confidence intervals for all parameters. The intervals are profile-likelihood confidence intervals, and are shown in the Solution report. The confidence limit computations involve a new set of iterations for each limit of each parameter, and the iterations often do not find the limits successfully. The Edit Alpha and Convergence Criterion options are for the confidence interval computations. For details about the Goal SSE for CL, see Profile Likelihood Confidence Limits.

SSE shows the residual sum of squares error. SSE is the objective that is to be minimized. If a custom loss function is specified, this is the sum of the loss function.

DFE is the degrees of freedom for error, which is the number of observations used minus the number of parameters fitted.

MSE shows the mean squared error. It is the estimate of the variance of the residual error, which is the SSE divided by the DFE.

RMSE estimates the standard deviation of the residual error, which is square root of the MSE.

Parameter lists the names that you gave the parameters in the fitting formula.

Estimate lists the parameter estimates produced. Keep in mind that with nonlinear regression, there might be problems with this estimate even if everything seems to work.

ApproxStdErr lists the approximate standard error, which is computed analogously to linear regression. It is formed by the product of the RMSE and the square root of the diagonals of the derivative cross-products matrix inverse.

Lower CL and Upper CL are the confidence limits for the parameters. They are missing until you click the Confidence Limits on the Control Panel. For more details about the confidence intervals, see Profile Likelihood Confidence Limits.

Excluded Data is a report showing fit statistics for excluded rows. This is useful for validating the model on observations not used to fit the model. You can use this feature in conjunction with the Remember Solution option to change the exclusions, and get a new report reflecting the different exclusions