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 46 of file FumiliMaximumLikelihoodFCN.h.

Public Member Functions
	FumiliMaximumLikelihoodFCN ()

	~FumiliMaximumLikelihoodFCN () override

virtual std::vector< double >	Elements (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.

virtual const std::vector< double > &	GetMeasurement (int Index) const =0
	Accessor to the parameters of a given measurement.

virtual int	GetNumberOfMeasurements () const =0
	Accessor to the number of measurements used for calculating the present figure of merit.

const ParametricFunction *	ModelFunction () const
	Returns the model function used for the data.

double	operator() (const std::vector< double > &par) const override
	Calculates the function for the maximum likelihood method.

void	SetModelFunction (const ParametricFunction &modelFCN)
	Sets the model function for the data (for example gaussian+linear for a peak)

double	Up () const override
	!!!!!!!!!!!! to be commented

Public Member Functions inherited from ROOT::Minuit2::FumiliFCNBase
	FumiliFCNBase ()
	Default Constructor.

	FumiliFCNBase (unsigned int npar)
	Constructor which initializes the class with the function provided by the user for modeling the data.

	~FumiliFCNBase () override

virtual unsigned int	Dimension ()
	return number of function variable (parameters) , i.e.

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.

virtual const std::vector< double > &	Gradient () const
	Return cached Value of function Gradient estimated previously using the FumiliFCNBase::EvaluateAll method.

std::vector< double >	Gradient (const std::vector< double > &) const override

std::vector< double >	Hessian (const std::vector< double > &) const override
	Return Value of the i-th j-th element of the Hessian matrix estimated previously using the FumiliFCNBase::EvaluateAll method.

virtual double	Hessian (unsigned int row, unsigned int col) const

virtual double	Value () const
	Return cached Value of objective function estimated previously using the FumiliFCNBase::EvaluateAll method.

Public Member Functions inherited from ROOT::Minuit2::FCNGradientBase
	~FCNGradientBase () override

virtual bool	CheckGradient () const

virtual std::vector< double >	G2 (const std::vector< double > &) const
	return second derivatives (diagonal of the Hessian matrix)

virtual std::vector< double >	GradientWithPrevResult (const std::vector< double > &parameters, double , double , double *) const

virtual GradientParameterSpace	gradParameterSpace () const

virtual bool	HasG2 () const

virtual bool	HasHessian () const

Public Member Functions inherited from ROOT::Minuit2::FCNBase
	~FCNBase () override

virtual double	ErrorDef () const
	Error definition of the function.

virtual void	SetErrorDef (double)
	add interface to set dynamically a new error definition Re-implement this function if needed.

Public Member Functions inherited from ROOT::Minuit2::GenericFunction
virtual	~GenericFunction ()

Private Attributes
const ParametricFunction *	fModelFunction

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

void	SetFCNValue (double value)

#include <Minuit2/FumiliMaximumLikelihoodFCN.h>

Inheritance diagram for ROOT::Minuit2::FumiliMaximumLikelihoodFCN:

[legend]

Constructor & Destructor Documentation

◆ FumiliMaximumLikelihoodFCN()

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

inline

Definition at line 49 of file FumiliMaximumLikelihoodFCN.h.

◆ ~FumiliMaximumLikelihoodFCN()

ROOT::Minuit2::FumiliMaximumLikelihoodFCN::~FumiliMaximumLikelihoodFCN ( )

inlineoverride

Definition at line 51 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

par	vector 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

Index Index of the measueremnt the parameters of which to return