[#1] INFO:Fitting -- RooAbsPdf::fitTo(mvg_over_mvg_Int[x0,x1,x2,x3]) fixing normalization set for coefficient determination to observables in data
[#1] INFO:Fitting -- using generic CPU library compiled with no vectorizations
[#1] INFO:Fitting -- Creation of NLL object took 7.12388 ms
[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_mvg_over_mvg_Int[x0,x1,x2,x3]_mvgData) Summation contains a RooNLLVar, using its error level
[#1] INFO:Minimization -- [fitFCN] No discrete parameters, performing continuous minimization only
Minuit2Minimizer: Minimize with max-calls 2000 convergence for edm < 1 strategy 1
Minuit2Minimizer : Valid minimum - status = 0
FVAL  = 706.560063684865781
Edm   = 9.79361268420962158e-06
Nfcn  = 68
mu_x0	  = 0.180728	 +/-  0.17298	(limited)
mu_x1	  = 0.207351	 +/-  0.172978	(limited)
mu_x2	  = -0.0159412	 +/-  0.172984	(limited)
mu_x3	  = 0.12343	 +/-  0.172982	(limited)
[#1] INFO:Fitting -- RooAbsPdf::fitTo(mvg_over_mvg_Int[x0,x1,x2,x3]) fixing normalization set for coefficient determination to observables in data
[#1] INFO:Fitting -- Creation of NLL object took 168.83 μs
Metropolis-Hastings progress: ....................................................................................................
[#1] INFO:Eval -- Proposal acceptance rate: 37.1%
[#1] INFO:Eval -- Number of steps in chain: 3710
[#1] INFO:InputArguments -- The deprecated RooFit::CloneData(1) option passed to createNLL() is ignored.
[#1] INFO:Fitting -- RooAbsPdf::fitTo(mvg_over_mvg_Int[x0,x1,x2,x3]) fixing normalization set for coefficient determination to observables in data
[#1] INFO:Fitting -- Creation of NLL object took 137.471 μs
[#0] PROGRESS:Minimization -- ProfileLikelihoodCalcultor::DoGLobalFit - find MLE 
[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_mvg_over_mvg_Int[x0,x1,x2,x3]_mvgData) Summation contains a RooNLLVar, using its error level
[#0] PROGRESS:Minimization -- ProfileLikelihoodCalcultor::DoMinimizeNLL - using Minuit2 / Migrad with strategy 1
[#1] INFO:Minimization -- [fitFCN] No discrete parameters, performing continuous minimization only
[#1] INFO:Minimization -- 
  RooFitResult: minimized FCN value: 706.56, estimated distance to minimum: 2.41067e-06
                covariance matrix quality: Full, accurate covariance matrix
                Status : MINIMIZE=0 

    Floating Parameter    FinalValue +/-  Error   
  --------------------  --------------------------
                 mu_x0    1.8134e-01 +/-  1.73e-01
                 mu_x1    2.0772e-01 +/-  1.73e-01
                 mu_x2   -1.5923e-02 +/-  1.73e-01
                 mu_x3    1.2360e-01 +/-  1.73e-01

[#1] INFO:Minimization -- RooProfileLL::evaluate(RooEvaluatorWrapper_Profile[mu_x1,mu_x0]) Creating instance of MINUIT
[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_mvg_over_mvg_Int[x0,x1,x2,x3]_mvgData) Summation contains a RooNLLVar, using its error level
[#1] INFO:Minimization -- RooProfileLL::evaluate(RooEvaluatorWrapper_Profile[mu_x1,mu_x0]) determining minimum likelihood for current configurations w.r.t all observable
[#1] INFO:Minimization -- [fitFCN] No discrete parameters, performing continuous minimization only
[#1] INFO:Minimization -- RooProfileLL::evaluate(RooEvaluatorWrapper_Profile[mu_x1,mu_x0]) minimum found at (mu_x0=0.181185, mu_x1=0.207918)
.[#1] INFO:Minimization -- [fitFCN] No discrete parameters, performing continuous minimization only
.[#1] INFO:Minimization -- [fitFCN] No discrete parameters, performing continuous minimization only
[#1] INFO:Minimization -- LikelihoodInterval - Finding the contour of mu_x1 ( 1 ) and mu_x0 ( 0 ) 
MCMC interval on p0: [-0.19999999999999996, 0.6000000000000001]
MCMC interval on p1: [-0.27999999999999997, 0.6000000000000001]
Real time 0:00:01, CP time 1.020