class ROOT::Fit::FitResult

      Default constructor for an empty (non valid) fit result

      Constructor from a fit-config for a dummy fit
      (e.g. when only one fcn evaluation is done)

      Construct from a Minimizer instance after fitting
      Run also Minos if requested from the configuration

      Copy constructor.

      Destructor

      Update the fit result with a new minimization status
      To be run only if same fit is performed with same configuration
      Note that in this case MINOS is not re-run. If one wants to run also MINOS
      a new result must be created

 minimization quantities 
 minimizer type

       True if fit successful, otherwise false.
       A fit is considered successful if the minimizer succeded in finding the
       minimum. It could happen that subsequent operations like error analysis (e.g. Minos)
       failed. In that case the status can be still true if the original minimization algorithm
       succeeded in finding the minimum.
       One can query in that case the minimizer return status using Status().
       It is responability to the Minimizer class to tag a found minimum as valid or not
       and to produce also a status code.

 True if a fit result does not exist (even invalid) with parameter values

 Return value of the objective function (chi2 or likelihood) used in the fit

Number of function calls to find minimum

Expected distance from minimum

   get total number of parameters

 total number of parameters (abbreviation)

 get total number of free parameters

 minimizer status code

covariance matrix status code
 using Minuit convention : =0 not calculated, =1 approximated, =2 made pos def , =3 accurate

 fitting quantities 
 Return pointer to model (fit) function with fitted parameter values.

 Chi2 fit value
 in case of likelihood must be computed ?

 Number of degree of freedom

 p value of the fit (chi2 probability)

 parameter errors (return st::vector)

 parameter errors (return const pointer)

 parameter values (return std::vector)

 parameter values (return const pointer)

 parameter value by index

 parameter value by index

 parameter error by index
 (NOTE: this due to conflict with TObject::Error cannot used in derived class which
 inherits from TObject. Use instead ParError (or Errors()[i] )

 parameter error by index

 name of the parameter

 set the Minos errors for parameter i (called by the Fitter class when running Minos)

 query if parameter i has the Minos error

 lower Minos error. If Minos has not run for parameter i return the parabolic error

 upper Minos error. If Minos has not run for parameter i return the parabolic error

 parameter global correlation coefficient

 retrieve covariance matrix element

 retrieve correlation elements

 fill covariance matrix elements using a generic matrix class implementing operator(i,j)
 the matrix must be previously allocates with right size (npar * npar)

 fill a correlation matrix elements using a generic symmetric matrix class implementing operator(i,j)
 the matrix must be previously allocates with right size (npar * npar)

      get confidence intervals for an array of n points x.
      stride1 indicates the stride in the coordinate space while stride2 the stride in dimension space.
      For 1-dim points : stride1=1, stride2=1
      for multi-dim points arranged as (x0,x1,...,xN,y0,....yN)          stride1=1      stride2=n
      for multi-dim points arraged  as (x0,y0,..,x1,y1,...,xN,yN,..)     stride1=ndim,  stride2=1

      the confidence interval are returned in the array ci
      cl is the desired confidedence interval value
      norm is a flag to control if the intervals need to be normalized to the chi2/ndf value
      By default the intervals are corrected using the chi2/ndf value of the fit if a chi2 fit is performed

      evaluate confidence interval for the point specified in the passed data sets
      the confidence interval are returned in the array ci
      cl is the desired confidence interval value

 get index for parameter name (return -1 if not found)

normalize errors using chi2/ndf for chi2 fits

 flag to chek if errors are normalized

 print the result and optionaly covariance matrix and correlations

print error matrix and correlations

 query if a parameter is bound

 query if a parameter is fixed

 retrieve parameter bounds - return false if parameter is not bound

 get name of parameter (deprecated)