The least-squares fitting tool provides an automatic method for
adjusting the parameters of your model so that it fits the data
better. It does this by using a non-linear optimization package to
minimize for the model and data.
Use the radio buttons at the top left to choose between fitting
amplitudes and phases and amplitudes only. The fields at the top are
updated during the fitting process and show the number of iterations
carried out so far, the number of times that has been
evaluated (function evaluations) and the current value of
divided by the number of data points. If the model fits the data
within the errors, the last number should be about 1.0.
The large text area at the bottom of the tool is used to report the results of the fit. This shows the conditions under which the fitting process ended and, if successful, the final parameter values and their standard errors (assuming that the data errors have a Gaussian distribution). As is the usual case, these errors represent the standard error in each parameter if only that parameter were in error: in reality, the parameters are not independent of each other and these error estimates will tend to underestimate the actual standard error for any given model parameter.
Start the fitting process by selecting the Fit Data command from the Fitter menu. A dialogue will appear to remind you that the model can not be changed while the fitting tool is working. This dialogue may not appear until the first iteration is complete which make take several minutes. You can use the Cancel button on this dialogue to stop the fitting tool at the earliest possible opportunity.
SLIME is unable to respond to any X events during an iteration of the model-fitting process so it will appear not to be working while an iteraction is being carried out. This may take anywhere from a few seconds to several minutes depending on the complexity of the model and the amout of data you are using. Don't attempt to kill SLIME if it appears to be hang during model fitting: it is still working.
The fitting procedure will report one of several reasons for ending when it has finished.
Irrespective of whether the fit was successful or not, the final parameters will become the current model parameters. If you don't like them for any reason, you can use the Undo function of the model editor to restore the parameters to their pre-fit state.