FCN=49.5952 FROM MIGRAD    STATUS=CONVERGED      52 CALLS          53 TOTAL
                     EDM=1.22682e-09    STRATEGY= 1  ERROR MATRIX UNCERTAINTY   2.5 per cent
  EXT PARAMETER                                   STEP         FIRST   
  NO.   NAME      VALUE            ERROR          SIZE      DERIVATIVE 
   1  p0           3.13201e+00   3.12699e-02  -3.64656e-05   2.15221e-03
   2  p1           2.97626e+01   1.00773e+00   6.67621e-05  -4.02033e-06
Integral = 19.005 +/- 0.6159
 
#include <assert.h>
#include <iostream>
#include <cmath>
 
 
const int NPAR = 2; 
 
double f(
double * 
x, 
double * p) {
 
   
}
 
void ErrorIntegral() {
   fitFunc = 
new TF1(
"f",
f,0,1,NPAR);
 
   double  par[NPAR] = { 3.14, 1.};
 
 
 
   
   double integral = fitFunc->
Integral(0,1);
 
 
   assert(fitter != 0);
 
   
 
   std::cout << "Integral = " << integral << " +/- " << sigma_integral
             << std::endl;
 
   
 
   double ic  = p[1]* (1-
std::cos(p[0]) )/p[0];
 
 
   
   double sic = 
std::sqrt( c0c*c0c * covMatrix[0] + c1c*c1c * covMatrix[3]
 
      + 2.* c0c*c1c * covMatrix[1]);
 
   if ( 
std::fabs(sigma_integral-sic) > 1.E-6*sic )
 
      std::cout << " ERROR: test failed : different analytical  integral : "
                << ic << " +/- " << sic << std::endl;
}
virtual Double_t Integral(Double_t a, Double_t b, Double_t epsrel=1.e-12)
IntegralOneDim or analytical integral.
virtual Double_t * GetParameters() const
virtual void SetParameters(const Double_t *params)
virtual void SetParameter(Int_t param, Double_t value)
virtual Double_t IntegralError(Double_t a, Double_t b, const Double_t *params=0, const Double_t *covmat=0, Double_t epsilon=1.E-2)
Return Error on Integral of a parametric function between a and b due to the parameter uncertainties.
1-D histogram with a double per channel (see TH1 documentation)}
virtual void FillRandom(const char *fname, Int_t ntimes=5000)
Fill histogram following distribution in function fname.
virtual TFitResultPtr Fit(const char *formula, Option_t *option="", Option_t *goption="", Double_t xmin=0, Double_t xmax=0)
Fit histogram with function fname.
virtual void Draw(Option_t *option="")
Draw this histogram with options.
Abstract Base Class for Fitting.
virtual Double_t * GetCovarianceMatrix() const =0
static TVirtualFitter * GetFitter()
static: return the current Fitter
VecExpr< UnaryOp< Fabs< T >, VecExpr< A, T, D >, T >, T, D > fabs(const VecExpr< A, T, D > &rhs)