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CAF123
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I am looking to perform a ##\chi^2## fit to more than one data set in mathematica, I just wondered how one would set this up?
Given some non-linear ansatz function ##F## depending on some parameters ##a,b,c## to describe all sets of data, i.e ##F = F_z(x,a,b,c)## I want to do a ##\chi^2## fit that will take all sets of data into account to get the best fit values of the parameters. So I just wondered how to do this in mathematica?
In the plot attached, the x argument above corresponds to the x-axis and F is the predicted value along the y axis. The upper most band of data corresponds to some value of z and the lower band of data corresponds to another value of z. a,b,c are my parameters that I would like the best estimate for. So essentially I'm looking for some simultaneous non-linear minimisation routine.
I am fairly new to mathematica so still getting to grips with it so apologies if my question is too simple from the outset.
Thanks!
Given some non-linear ansatz function ##F## depending on some parameters ##a,b,c## to describe all sets of data, i.e ##F = F_z(x,a,b,c)## I want to do a ##\chi^2## fit that will take all sets of data into account to get the best fit values of the parameters. So I just wondered how to do this in mathematica?
In the plot attached, the x argument above corresponds to the x-axis and F is the predicted value along the y axis. The upper most band of data corresponds to some value of z and the lower band of data corresponds to another value of z. a,b,c are my parameters that I would like the best estimate for. So essentially I'm looking for some simultaneous non-linear minimisation routine.
I am fairly new to mathematica so still getting to grips with it so apologies if my question is too simple from the outset.
Thanks!