can somebody explain the multi-branch fit option a bit more? I would like to fit three experimental data sets to three functions with two common variables.
Is this possible?
The example only shows how to do this for 2 data sets...
It's hard to offer better explanations without knowing where and how the existing ones failed you. It's really quite simple: multi-branch fits are 3D fits, e.g. they fit data to a model z=f(x,y). The trick is that we have several different meanings of 'x', and we use 'y' to decide which of them to apply.
Please have a look at both "help fit multi-branch" and at the fit.dem examples.
thanks for replying to my message. I managed to fit my two functions with the two variables to TWO data sets - I would simply like to extend the
(y==0) ? A(x):B(x) to three data sets and three functions with the two common variables.
(y==0) ? A(x):B(x):C(x) obviously does not work, so it should be something along the line of
(y==0) ? A(x):B(x) AND
(y==1) ? B(x):C(x)... etc. really only needs a proper assignment of the 3D variable y to check for 0, 1 or 2.
Any help is appreciated...
I managed to fit three data sets with three functions with two unknown variables by using
f(x,y) = (y == 0) ? h1(x) : ((y==1) ? h2(x) : h3(x))
fit f(x,y) 'syn_10_20_40.txt' using 1:-2:2:(1) via var1, var2
Thanks for your help.