class TBackCompFitter: public TVirtualFitter

 Constructur needed by TVirtualFitter interface. Same behavior as default constructor.
 initialize setting name and the global pointer

 constructor used after having fit using directly ROOT::Fit::Fitter
 will create a dummy fitter copying configuration and parameter settings

 data are own here
if (fFitData) delete fFitData;

 do chisquare calculations in case of likelihood fits
 do evaluation a the minimum only

 clear resources for consecutive fits

 execute the command (Fortran Minuit compatible interface)

 check if ipar is a valid parameter index

 fix the paramter
   std::cout<<"FixParameter"<<std::endl;

Computes point-by-point confidence intervals for the fitted function
Parameters:
n - number of points
ndim - dimensions of points
x - points, at which to compute the intervals, for ndim > 1
    should be in order: (x0,y0, x1, y1, ... xn, yn)
ci - computed intervals are returned in this array
cl - confidence level, default=0.95
NOTE, that the intervals are approximate for nonlinear(in parameters) models

Computes confidence intervals at level cl. Default is 0.95
The TObject parameter can be a TGraphErrors, a TGraph2DErrors or a TH1,2,3.
For Graphs, confidence intervals are computed for each point,
the value of the graph at that point is set to the function value at that
point, and the graph y-errors (or z-errors) are set to the value of
the confidence interval at that point.
For Histograms, confidence intervals are computed for each bin center
The bin content of this bin is then set to the function value at the bin
center, and the bin error is set to the confidence interval value.
NOTE: confidence intervals are approximate for nonlinear models!

Allowed combinations:
Fitted object               Passed object
TGraph                      TGraphErrors, TH1
TGraphErrors, AsymmErrors   TGraphErrors, TH1
TH1                         TGraphErrors, TH1
TGraph2D                    TGraph2DErrors, TH2
TGraph2DErrors              TGraph2DErrors, TH2
TH2                         TGraph2DErrors, TH2
TH3                         TH3

 get the error matrix in a pointer to a NxN array.
 excluding the fixed parameters

 get error matrix element

 get fit errors

 number of total parameters

 number of variable parameters

 parameter error

 parameter value

 get all parameter info (name, value, errors)

   return name of parameter ipar

 get fit statistical information

   sum of log . Un-needed

 query if parameter ipar is fixed

 print the fit result
 use PrintResults function in case of Minuit for old -style printing

 release a fit parameter

 set fit method (i.e. chi2 or likelihood)
 according to the method the appropriate FCN function will be created

 set (add) a new fit parameter passing initial value,  step size (verr) and parametr limits
 if vlow > vhigh the parameter is unbounded
 if the stepsize (verr) == 0 the parameter is treated as fixed

 set objective function in minimizers function to re-create FCN from stored data object and fit options

 override setFCN to use the Adapter to Minuit2 FCN interface
To set the address of the minimization function*-
*-*          ===============================================
*

To set the address of the minimization function*-
*-*          ===============================================
     this function is called by CINT instead of the function above
*

 class clone a copy of the function

 set dimension in objective function

     scan parameter ipar between value of xmin and xmax
     a graph must be given which will be on return filled with the scan resul
     If the graph size is zero, a default size n = 40 will be used
*

  create a 2D contour around the minimum for the parameter ipar and jpar
 if a minimum does not exist or is invalid it will return false
 on exit a TGraph is filled with the contour points
 the number of contur points is determined by the size of the TGraph.
 if the size is zero a default number of points = 20 is used
 pass optionally the confidence level, default is 0.683
 it is assumed that ErrorDef() defines the right error definition
 (i.e 1 sigma error for one parameter). If not the confidence level are scaled to new level

 for using interpreted function passed by the user

!!!! new method (of this interface)
 get reference to Fit configuration (NOTE: it will be invalid when class is deleted)

 get reference to Fit Result object (NOTE: it will be invalid when class is deleted)