Backwards elimination of parameters to see if any variable parameters can safely be eliminated. Comprehensive statistical and error analyses give confidence limits on fitted parameters. Includes covariances and Monte Carlo simulation. In many cases this method can linearise the function for you. DataFit calculates analytical derivatives with respect to each parameter, to achieve rapid convergence speeds.
Genetic algorithm uses an analogy of evolution and mutation to generate probable solutions.
Interactive graphical fitting lets you change the parameter values manually, and watch in real time how they affect the fitted function. Plot the fitted function, or plot the error residuals vs the dependent or independent variables. Monte Carlo simulation for precise estimates of confidence intervals on fitted parameters. Selecting a suitable function Several options are available to help find a suitable function to fit to your data. Fit any number of user-definable functions from disk files and rank them in order.