Abnormal termination of minimization with TF1::Fit

dear ROOTERs!

I have a problem. I am using ROOT 3.10 and doing a multicombined with with 60 parameters.
I am using by default Tf1::Fit wwhich uses by default MIGRAD, which is considered to be good enough for most(but not all) the cases.
But it fails me, just take a look at the first couple of lines of output of ROOT after executing my program:

root [0] .x show10n.C
Warning in TH1F::Fit: Abnormal termination of minimization.
FCN=351.334 FROM MIGRAD STATUS=CALL LIMIT 27241 CALLS 27242 TOTAL
EDM= unknown STRATEGY= 1 NO ERROR MATRIX
EXT PARAMETER CURRENT GUESS STEP FIRST
NO. NAME VALUE ERROR SIZE DERIVATIVE
1 p0 6.09596e+00 1.82879e+00 0.00000e+00 0.00000e+00
2 p1 1.00000e+00 3.00000e-01 0.00000e+00 0.00000e+00
3 p2 5.72000e-02 1.71600e-02 0.00000e+00 6.20661e-04
4 p3 6.54690e+04 1.96407e+04 0.00000e+00 0.00000e+00
5 p4 2.00000e+00 6.00000e-01 0.00000e+00 0.00000e+00
6 p5 1.90000e-01 5.70000e-02 0.00000e+00 0.00000e+00
7 p6 2.32986e+03 6.98958e+02 0.00000e+00 0.00000e+00
8 p7 3.00000e+00 9.00000e-01 0.00000e+00 0.00000e+00
9 p8 1.80000e-01 5.40000e-02 0.00000e+00 0.00000e+00
10 p9 1.10414e+02 3.31242e+01 0.00000e+00 0.00000e+00
11 p10 4.00000e+00 1.20000e+00 0.00000e+00 -7.14682e+00
12 p11 5.80000e-02 1.74000e-02 0.00000e+00 0.00000e+00
13 p12 1.26000e+03 3.78000e+02 0.00000e+00 -4.60180e-02
14 p13 5.00000e+00 1.50000e+00 0.00000e+00 -8.32872e+02
15 p14 1.80000e-01 5.40000e-02 0.00000e+00 -2.16832e+03
16 p15 1.99500e+03 5.98500e+02 0.00000e+00 -5.70621e-01
17 p16 6.00000e+00 1.80000e+00 0.00000e+00 8.19720e+02
18 p17 1.90000e-01 5.70000e-02 0.00000e+00 -1.43596e+04

But the point is that the data and the fitting function are matching quite good and you would never think that something is wrong. I am doing a combined fit with gauss so p0,p3,p6 … are the first parameter of gauss(height), p1,p4,p7 etc is mean and p2,p5 etc sigma.
I was told to use another algorithm. So can you please help me resolve this issue. Or should I maybe use not TMinuit but something else to fit?

thanks in advance,
Regards
Hayk Hakobyan

Hi,

Which other algorithm were you old to use ?

Eddy

Hi Eddie,

I used Minos and already resolved the issue. The probelm was that MIGRAD was unable to do a correct error estimates for 60 parameters although it was displaying a perfect fit. With Minosit takes more time but it does a good error estimate.

Thanks and Regards

Hayk Hakobyan