Fitting with dependent variable in model expr

When trying to combine data taken in two independent experiments, I ran across the following problem when fitting:

 z(P) = w(z)*f(P)

w(z) is known in the form of a cfit object, z is the dependent and P the independent from a set of data.

My first thoughts were to invert the function to obtain P(z) rather than z(P) and then to use eval in the model, but I can't figure out the proper way to formulate the fittype model to allow for this sort of behavior.

Does anybody know how to do this? I need a few pointers :)

Answer 1

[Niko]

I solved the first problem by inverting my data, and fitting an inverted function of the form

P(z) = f^-1(z) * g(w(z))

with f,g being the appropriate functions for this transformation. The remaining question is how to do this in matlab:

Fittype with expr (w is a cfit object)

'z/feval(w,z)'

or

'z/w(z)'

throws an error:

is not a valid MATLAB expression,
has non-scalar coefficients, or cannot be evaluated