ROOT 6.10/09 Reference Guide 
#include "TFumili.h"
#include "Riostream.h"
#include "TGraphAsymmErrors.h"
#include "TF1.h"
#include "TF2.h"
#include "TF3.h"
#include "TH1.h"
#include "TMath.h"
#include "TROOT.h"
#include "TVirtualFitter.h"
Functions  
void  GraphFitChisquareFumili (Int_t &npar, Double_t *gin, Double_t &f, Double_t *u, Int_t flag) 
*****Minimization function for Graphs using a Chisquare method**** ** ========================================================= More...  
void  H1FitChisquareFumili (Int_t &npar, Double_t *gin, Double_t &f, Double_t *u, Int_t flag) 
Minimization function for H1s using a Chisquare methodMore...  
void  H1FitLikelihoodFumili (Int_t &npar, Double_t *gin, Double_t &f, Double_t *u, Int_t flag) 
****Minimization function for H1s using a Likelihood method******Basically, it forms the likelihood by determining the Poisson probability that given a number of entries in a particular bin, the fit would predict it's value. More...  
Variables  
TFumili *  gFumili =0 
static const Double_t  gMAXDOUBLE =1e300 
static const Double_t  gMINDOUBLE =1e300 
void GraphFitChisquareFumili  (  Int_t &  npar, 
Double_t *  gin,  
Double_t &  f,  
Double_t *  u,  
Int_t  flag  
) 
*****Minimization function for Graphs using a Chisquare method**** ** =========================================================
In case of a TGraphErrors object, ex, the error along x, is projected along the ydirection by calculating the function at the points xexlow and x+exhigh.
The chisquare is computed as the sum of the quantity below at each point:
(y  f(x))**2  ey**2 + (0.5*(exl + exh)*f'(x))**2
where x and y are the point coordinates and f'(x) is the derivative of function f(x). This method to approximate the uncertainty in y because of the errors in x, is called "effective variance" method. The improvement, compared to the previously used method (f(x+ exhigh)  f(xexlow))/2 is of (error of x)**2 order. NOTE: 1) By using the "effective variance" method a simple linear regression becomes a nonlinear case , which takes several iterations instead of 0 as in the linear case .
2) The effective variance technique assumes that there is no correlation between the x and y coordinate .
In case the function lies below (above) the data point, ey is ey_low (ey_high).
Definition at line 2149 of file TFumili.cxx.
Definition at line 2092 of file TFumili.cxx.
This is then done for each bin, and the sum of the logs is taken as the likelihood. PDF: P=exp(f(x_i))/[F_i]!*(f(x_i))^[F_i] where F_i  experimental value, f(x_i)  expected theoretical value [F_i]  integer part of F_i. drawback is that if F_i>Int_t  GetSumLog will fail for big F_i is faster to use Euler's Gammafunction
Definition at line 2111 of file TFumili.cxx.
TFumili* gFumili =0 
Definition at line 120 of file TFumili.cxx.

static 
Definition at line 123 of file TFumili.cxx.

static 
Definition at line 124 of file TFumili.cxx.