Dear experts,
I know that, when the error matrix is not positive-definite, this is an indication of a strong correlation among parameters.
In addition to that, I have an additional, strange problem: after the fit, the “fitted” parameters have exactly the same values I gave them as initial conditions.
Is this still related to parameter correlations, or there is something else I should check?
This is the final printout:
FCN=-8.71049 FROM HESSE STATUS=NOT POSDEF 135 CALLS 546 TOTAL
EDM=8.04748e+08 STRATEGY= 2 ERR MATRIX NOT POS-DEF
EXT PARAMETER APPROXIMATE INTERNAL INTERNAL
NO. NAME VALUE ERROR STEP SIZE VALUE
1 Ipatia_BeautyMass_mean_Signal_Bd2DPiHypo 5.28012e+03 1.83275e-03 2.46768e-05 6.83198e-02
2 Ipatia_BeautyMass_sigma_Signal_Bd2DPiHypo 2.05007e+01 9.44771e-04 4.26240e-04 1.00308e-01
3 eff_Bd2DK_DK 6.36204e-01 3.14465e-05 1.70299e-03 -9.21058e-02
4 eff_Bd2DPi_DPi 9.78950e-01 1.41049e-04 2.16958e-07 9.09988e-01
5 nEvts_Bd2DK_Bd2DKHypo 4.50000e+04 3.61784e+01 1.66661e-06 -1.14328e+00
6 nEvts_Bd2DKst_Bd2DKHypo 5.00000e+03 4.72029e+01 3.26743e-07 -1.37046e+00
7 nEvts_Bd2DPi_Bd2DPiHypo 4.50000e+05 1.09657e+02 8.36650e-05 -1.00167e-01
8 nEvts_Bd2DRho_Bd2DKHypo 1.00000e+04 1.12117e+02 3.06845e-07 -1.28700e+00
9 nEvts_Bd2DRho_Bd2DPiHypo 7.00000e+04 2.14037e+01 2.01838e-06 -1.03527e+00
10 nEvts_Bd2DstPi_Bd2DPiHypo 5.00000e+04 2.11194e+01 1.09008e-04 -1.11977e+00
11 nEvts_Comb_Bd2DKHypo 1.50000e+03 3.51283e+05 3.48377e-07 -1.46120e+00
12 nEvts_Comb_Bd2DPiHypo 1.50000e+04 1.29068e+01 3.15960e-07 -1.32523e+00
This is the correlation matrix:
PARAMETER CORRELATION COEFFICIENTS
NO. GLOBAL 1 2 3 4 5 6 7 8 9 10 11 12
1 0.00099 1.000 0.000 -0.000 -0.001 0.001 0.001 0.001 0.001 0.000 0.000 -0.001 -0.000
2 0.00058 0.000 1.000 0.000 0.000 -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 0.000 -0.000
3 0.00079 -0.000 0.000 1.000 -0.001 0.001 0.001 0.001 0.001 0.000 0.000 -0.001 0.000
4 0.99764 -0.001 0.000 -0.001 1.000 -0.911 -0.991 -0.933 -0.995 0.001 0.000 0.998 0.002
5 0.91344 0.001 -0.000 0.001 -0.911 1.000 0.908 0.855 0.911 -0.001 -0.000 -0.913 -0.002
6 0.99368 0.001 -0.000 0.001 -0.991 0.908 1.000 0.930 0.991 -0.001 -0.000 -0.994 -0.002
7 0.93567 0.001 -0.000 0.001 -0.933 0.855 0.930 1.000 0.933 -0.001 -0.000 -0.936 -0.002
8 0.99744 0.001 -0.000 0.001 -0.995 0.911 0.991 0.933 1.000 -0.001 -0.000 -0.997 -0.002
9 0.00436 0.000 -0.000 0.000 0.001 -0.001 -0.001 -0.001 -0.001 1.000 -0.004 0.001 -0.001
10 0.00442 0.000 -0.000 0.000 0.000 -0.000 -0.000 -0.000 -0.000 -0.004 1.000 0.000 -0.001
11 0.99900 -0.001 0.000 -0.001 0.998 -0.913 -0.994 -0.936 -0.997 0.001 0.000 1.000 0.002
12 0.00250 -0.000 -0.000 0.000 0.002 -0.002 -0.002 -0.002 -0.002 -0.001 -0.001 0.002 1.000
Thanks for your help.
Vincenzo