fit data(measurements) with numerical datasets

I have some data for which I have a set of numerically determined model curves. Now I would like to find the one w开发者_开发百科ith least square deviation, I only need to vary one parameter, which is the amplitude of these model curves.

I used fitting with analytic functions, but I did not find a way to handle such a problem.

Is there any solution?

Thanks a lot!

One of the optimize functions should do the trick. You can also read the section on optimization in the manual. Without any specifics on the data or the model you wish to match, it's hard to recommend anything more specific. For example, if your cost function has many maxima and minima or is not differentiable, you'll have to choose some of the more expensive routines.