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Reference Guide
ROOT::Minuit2::FumiliMaximumLikelihoodFCN Class Referenceabstract

Extension of the FCNBase for the Fumili method.

Fumili applies only to minimization problems used for fitting. The method is based on a linearization of the model function negleting second derivatives. User needs to provide the model function. In this cased the function to be minimized is the sum of the logarithms of the model function for the different measurements times -1.

Author
Andras Zsenei and Lorenzo Moneta, Creation date: 3 Sep 2004
See also
MINUIT Tutorial on function minimization, section 5
FumiliStandardMaximumLikelihoodFCN

Definition at line 51 of file FumiliMaximumLikelihoodFCN.h.

Public Member Functions

 FumiliMaximumLikelihoodFCN ()
 
virtual ~FumiliMaximumLikelihoodFCN ()
 
virtual std::vector< doubleElements (const std::vector< double > &par) const =0
 Evaluates the model function for the different measurement points and the Parameter values supplied, calculates a figure-of-merit for each measurement and returns a vector containing the result of this evaluation. More...
 
virtual const std::vector< double > & GetMeasurement (int Index) const =0
 Accessor to the parameters of a given measurement. More...
 
virtual int GetNumberOfMeasurements () const =0
 Accessor to the number of measurements used for calculating the present figure of merit. More...
 
const ParametricFunctionModelFunction () const
 Returns the model function used for the data. More...
 
double operator() (const std::vector< double > &par) const
 Calculates the function for the maximum likelihood method. More...
 
void SetModelFunction (const ParametricFunction &modelFCN)
 Sets the model function for the data (for example gaussian+linear for a peak) More...
 
virtual double Up () const
 !!!!!!!!!!!! to be commented More...
 
- Public Member Functions inherited from ROOT::Minuit2::FumiliFCNBase
 FumiliFCNBase ()
 Default Constructor. More...
 
 FumiliFCNBase (unsigned int npar)
 Constructor which initializes the class with the function provided by the user for modeling the data. More...
 
virtual ~FumiliFCNBase ()
 
virtual unsigned int Dimension ()
 return number of function variable (parameters) , i.e. More...
 
virtual void EvaluateAll (const std::vector< double > &par)=0
 Evaluate function Value, Gradient and Hessian using Fumili approximation, for values of parameters p The resul is cached inside and is return from the FumiliFCNBase::Value , FumiliFCNBase::Gradient and FumiliFCNBase::Hessian methods. More...
 
virtual const std::vector< double > & Gradient () const
 Return cached Value of function Gradient estimated previously using the FumiliFCNBase::EvaluateAll method. More...
 
virtual double Hessian (unsigned int row, unsigned int col) const
 Return Value of the i-th j-th element of the Hessian matrix estimated previously using the FumiliFCNBase::EvaluateAll method. More...
 
virtual double Value () const
 Return cached Value of objective function estimated previously using the FumiliFCNBase::EvaluateAll method. More...
 
- Public Member Functions inherited from ROOT::Minuit2::FCNBase
virtual ~FCNBase ()
 
virtual double ErrorDef () const
 Error definition of the function. More...
 
virtual double operator() (const std::vector< double > &x) const =0
 The meaning of the vector of parameters is of course defined by the user, who uses the values of those parameters to calculate their function Value. More...
 
virtual void SetErrorDef (double)
 add interface to set dynamically a new error definition Re-implement this function if needed. More...
 
virtual double Up () const =0
 Error definition of the function. More...
 
- Public Member Functions inherited from ROOT::Minuit2::GenericFunction
virtual ~GenericFunction ()
 
virtual double operator() (const std::vector< double > &x) const =0
 Evaluates the function using the vector containing the input values. More...
 

Private Attributes

const ParametricFunctionfModelFunction
 

Additional Inherited Members

- Protected Member Functions inherited from ROOT::Minuit2::FumiliFCNBase
std::vector< double > & Gradient ()
 
std::vector< double > & Hessian ()
 
virtual void InitAndReset (unsigned int npar)
 initialize and reset values of gradien and Hessian More...
 
void SetFCNValue (double value)
 

#include <Minuit2/FumiliMaximumLikelihoodFCN.h>

Inheritance diagram for ROOT::Minuit2::FumiliMaximumLikelihoodFCN:
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Constructor & Destructor Documentation

◆ FumiliMaximumLikelihoodFCN()

ROOT::Minuit2::FumiliMaximumLikelihoodFCN::FumiliMaximumLikelihoodFCN ( )
inline

Definition at line 55 of file FumiliMaximumLikelihoodFCN.h.

◆ ~FumiliMaximumLikelihoodFCN()

virtual ROOT::Minuit2::FumiliMaximumLikelihoodFCN::~FumiliMaximumLikelihoodFCN ( )
inlinevirtual

Definition at line 57 of file FumiliMaximumLikelihoodFCN.h.

Member Function Documentation

◆ Elements()

virtual std::vector< double > ROOT::Minuit2::FumiliMaximumLikelihoodFCN::Elements ( const std::vector< double > &  par) const
pure virtual

Evaluates the model function for the different measurement points and the Parameter values supplied, calculates a figure-of-merit for each measurement and returns a vector containing the result of this evaluation.

Parameters
parvector of Parameter values to feed to the model function.
Returns
A vector containing the figures-of-merit for the model function evaluated for each set of measurements.

Implemented in ROOT::Minuit2::FumiliStandardMaximumLikelihoodFCN.

◆ GetMeasurement()

virtual const std::vector< double > & ROOT::Minuit2::FumiliMaximumLikelihoodFCN::GetMeasurement ( int  Index) const
pure virtual

Accessor to the parameters of a given measurement.

For example in the case of a chi-square fit with a one-dimensional Gaussian, the Parameter characterizing the measurement will be the position. It is the Parameter that is feeded to the model function.

Parameters
IndexIndex of the measueremnt the parameters of which to return
Returns
A vector containing the values characterizing a measurement

Implemented in ROOT::Minuit2::FumiliStandardMaximumLikelihoodFCN.

◆ GetNumberOfMeasurements()

virtual int ROOT::Minuit2::FumiliMaximumLikelihoodFCN::GetNumberOfMeasurements ( ) const
pure virtual

Accessor to the number of measurements used for calculating the present figure of merit.

Returns
the number of measurements

Implemented in ROOT::Minuit2::FumiliStandardMaximumLikelihoodFCN.

◆ ModelFunction()

const ParametricFunction * ROOT::Minuit2::FumiliMaximumLikelihoodFCN::ModelFunction ( ) const
inline

Returns the model function used for the data.

Returns
Returns a pointer to the model function.

Definition at line 80 of file FumiliMaximumLikelihoodFCN.h.

◆ operator()()

double ROOT::Minuit2::FumiliMaximumLikelihoodFCN::operator() ( const std::vector< double > &  par) const
inlinevirtual

Calculates the function for the maximum likelihood method.

The user must implement in a class which inherits from FumiliChi2FCN the member function Elements() which will supply the Elements for the sum.

Parameters
parvector containing the Parameter values for the model function
Returns
The sum of the natural logarithm of the Elements multiplied by -1
See also
FumiliFCNBase::elements

Implements ROOT::Minuit2::FCNBase.

Definition at line 144 of file FumiliMaximumLikelihoodFCN.h.

◆ SetModelFunction()

void ROOT::Minuit2::FumiliMaximumLikelihoodFCN::SetModelFunction ( const ParametricFunction modelFCN)
inline

Sets the model function for the data (for example gaussian+linear for a peak)

Parameters
modelFunctiona reference to the model function.

Definition at line 68 of file FumiliMaximumLikelihoodFCN.h.

◆ Up()

virtual double ROOT::Minuit2::FumiliMaximumLikelihoodFCN::Up ( ) const
inlinevirtual

!!!!!!!!!!!! to be commented

Implements ROOT::Minuit2::FCNBase.

Definition at line 170 of file FumiliMaximumLikelihoodFCN.h.

Member Data Documentation

◆ fModelFunction

const ParametricFunction* ROOT::Minuit2::FumiliMaximumLikelihoodFCN::fModelFunction
private

Definition at line 175 of file FumiliMaximumLikelihoodFCN.h.

Libraries for ROOT::Minuit2::FumiliMaximumLikelihoodFCN:
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The documentation for this class was generated from the following file: