Hello everyone,

I am trying to implement the student-t function with the following functional form in Roofit:

$\frac{\Gamma \left( \frac{r+1}{2} \right)}{\Gamma \left( \frac{r}{2} \right)}\frac{1}{\sigma\sqrt[2]{\pi r}} \big{ 1 + \frac{(\Delta M -\overline{x}_{t})^{2}}{r\sigma^{2}} \big}^{-(\frac{r+1}{2})}$

where deltam is fit variable and sigma, xbar and r are shape parameters.

I am using RooGenericPdf for implementing this pdf. My fit pdf is a combination of (**gauss+gauss+student-t**) and I am performing unbinned extended maximum likelihood fit. I get a lot of errors which can be summarized into the following:

1> [#0] WARNING:Eval – RooAddPdf::updateCoefCache(dg_mdz1 WARNING: sum of PDF coefficients not in range [0-1], value=1.44797[#0] WARNING:Eva\

2>p.d.f normalization integral is zero or negative @ actualVars=(deltam = 0.145328,r = -2.67885,meant = 0.144452,sigmat = 0.00179944)

3> p.d.f value is Not-a-Number (nan), forcing value to zero @ actualVars=(deltam = 0.145898,r = -0.311657,meant = 0.147132,sigmat = 0.00115821)

4> getLogVal() top-level p.d.f evaluates to zero @ !refCoefNorm=(), !pdfs=(dg_mdz1 = -0.393874/1), !coefficients=(nsig = 9.15084e+06)

But after all these errors repeated multiple times MIGRAD converged and MINOS get STATUS = successful and error matrix accurate. Should I be worried about all those errors or just ignore them and use the final result ??

I am attaching the fit logsignal1d_yieldc.txt (174.4 KB)

final fit plot deltam_signal_1d_yieldchange.pdf (38.5 KB)

fitting code deltam_signal.C (10.1 KB)

dataset used: signal_new.txt (2.1 MB)

Please let me know if the query is not clear or any further information is required.

Aman