Hi everyone,
I ran into this fitting problem today. I am using ROOT 5.22, and trying to fit a Gaussian to a data distribution. I found that by adding the option M in the Fit function, i.e.
TF1 *f1 = new TF1("f1", "gaus",xMin, xMax);
f1->SetParameter(1,1);
f1->SetParameter(2,0.3);
f1->SetParameter(0,5000);
Int_t fitStatus1= h3->Fit(f1,"MR");
then fitStatus1 = 4000 and I have the following output:
[code] FCN=4.10816 FROM IMProve STATUS=RESET 16 CALLS 115 TOTAL
EDM=5.17398e-10 STRATEGY= 1 ERROR MATRIX UNCERTAINTY 50.0 per cent
EXT PARAMETER APPROXIMATE STEP FIRST
NO. NAME VALUE ERROR SIZE DERIVATIVE
1 Constant 7.17478e+01 4.45681e+00 4.45681e-02 -2.42411e-01
2 Mean 9.37711e-01 2.47538e-02 2.47538e-04 5.10127e+01
3 Sigma 2.02001e-01 3.47116e-02 3.47116e-04 -3.56969e+00
[/code]
But if I don’t add the M option, then fitStatus1 = 0 (according to the reference this means the fit is OK) and I get an output like:
FCN=3.45335 FROM MIGRAD STATUS=CONVERGED 77 CALLS 78 TOTAL
EDM=9.06247e-10 STRATEGY= 1 ERROR MATRIX UNCERTAINTY 1.9 per cent
EXT PARAMETER STEP FIRST
NO. NAME VALUE ERROR SIZE DERIVATIVE
1 Constant 7.45107e+01 5.02489e+00 -1.20113e-03 -7.85228e-06
2 Mean 9.40173e-01 1.44652e-02 9.12124e-06 1.51980e-03
3 Sigma 1.64264e-01 2.47823e-02 -1.05923e-04 1.77035e-04But the problem is, the M option actually give me a gaussian mean close to what I’d expect for some of the distributions, whereas the no-M option gives a mean that’s slightly different. The attached graph shows the difference between the two fitting methods.
Can I trust the result given by the M option?
c1.ps (13.4 KB)