Fitting parameters of the model against data

I have to fit parameters of my model against the data I have. My model equation is of the form,

z = ax / (by - c)

where a, b, c are the parameters and x, y, z forms variables.

Is that possible to fit the optimal parameter values if I have the data of x, y and z, in Julia? And using what packages?

Thanks in advance!

One of the most fundamental types of fitting algorithms you can start off with is nonlinear least squares. Take a look at GitHub - pjabardo/CurveFit.jl: Simple least squares and curve fitting functions which has an implementation you can use.

Edit: I recommend GitHub - JuliaNLSolvers/LsqFit.jl: Simple curve fitting in Julia over CurveFit.jl. Thanks for the suggestion @sylvaticus

Thanks for the suggestion. Will check it out.

Or the same kind of package, but perhaps more used: LsqFit.jl