Class implementing the Elements member function for the standard maximum likelihood method.

Author: Andras Zsenei and Lorenzo Moneta, Creation date: 4 Sep 2004

See also: FumiliMaximumLikelihoodFCN

Definition at line 34 of file FumiliStandardMaximumLikelihoodFCN.h.

Public Member Functions
	FumiliStandardMaximumLikelihoodFCN (const ParametricFunction &modelFCN, std::span< const double > pos)
	Constructor which initializes the measurement points for the one dimensional model function.
	FumiliStandardMaximumLikelihoodFCN (const ParametricFunction &modelFCN, std::span< const std::vector< double > > pos)
	Constructor which initializes the measurement points for the multi dimensional model function.
virtual unsigned int	Dimension ()
	return number of function variable (parameters) , i.e.
std::vector< double >	Elements (std::vector< double > const &par) const override
	Evaluates the model function for the different measurement points and the Parameter values supplied.
virtual double	ErrorDef () const
	Error definition of the function.
void	EvaluateAll (std::vector< double > const &par) override
	Evaluate function Value, Gradient and Hessian using Fumili approximation, for values of parameters p The result is cached inside and is return from the FumiliFCNBase::Value , FumiliFCNBase::Gradient and FumiliFCNBase::Hessian methods.
virtual std::vector< double >	G2 (std::vector< double > const &) const
	Return the diagonal elements of the Hessian (second derivatives).
const std::vector< double > &	GetMeasurement (int Index) const override
	Accessor to the position of the measurement (x coordinate).
int	GetNumberOfMeasurements () const override
	Accessor to the number of measurements used for calculating the maximum likelihood.
virtual const std::vector< double > &	Gradient () const
	Return cached Value of function Gradient estimated previously using the FumiliFCNBase::EvaluateAll method.
std::vector< double >	Gradient (std::vector< double > const &) const override
	Return the gradient vector of the function at the given parameter point.
virtual std::vector< double >	GradientWithPrevResult (std::vector< double > const &parameters, double , double , double *) const
virtual GradientParameterSpace	gradParameterSpace () const
virtual bool	HasG2 () const
bool	HasGradient () const override
virtual bool	HasHessian () const
std::vector< double >	Hessian (std::vector< double > const &) 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
const ParametricFunction *	ModelFunction () const
	Returns the model function used for the data.
double	operator() (std::vector< double > const &par) const override
	Calculates the function for the maximum likelihood method.
virtual void	SetErrorDef (double)
	add interface to set dynamically a new error definition Re-implement this function if needed.
void	SetModelFunction (const ParametricFunction &modelFCN)
	Sets the model function for the data (for example gaussian+linear for a peak).
double	Up () const override
	!
virtual double	Value () const
	Return cached Value of objective function estimated previously using the FumiliFCNBase::EvaluateAll method.

Protected Member Functions
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)

Private Attributes
std::vector< double >	fGradient
std::vector< double >	fHessian
const ParametricFunction *	fModelFunction
unsigned int	fNumberOfParameters
std::vector< std::vector< double > >	fPositions
double	fValue

#include <Minuit2/FumiliStandardMaximumLikelihoodFCN.h>

Inheritance diagram for ROOT::Minuit2::FumiliStandardMaximumLikelihoodFCN:

Constructor & Destructor Documentation

◆ FumiliStandardMaximumLikelihoodFCN() [1/2]

ROOT::Minuit2::FumiliStandardMaximumLikelihoodFCN::FumiliStandardMaximumLikelihoodFCN	(	const ParametricFunction &	modelFCN,
		std::span< const double >	pos )

inline

Constructor which initializes the measurement points for the one dimensional model function.

Parameters

modelFCN	the model function used for describing the data.
pos	vector containing the x values corresponding to the measurements

Definition at line 48 of file FumiliStandardMaximumLikelihoodFCN.h.

◆ FumiliStandardMaximumLikelihoodFCN() [2/2]

ROOT::Minuit2::FumiliStandardMaximumLikelihoodFCN::FumiliStandardMaximumLikelihoodFCN	(	const ParametricFunction &	modelFCN,
		std::span< const std::vector< double > >	pos )

inline

Constructor which initializes the measurement points for the multi dimensional model function.

Parameters

modelFCN	the model function used for describing the data.
pos	vector containing the x values corresponding to the measurements

Definition at line 71 of file FumiliStandardMaximumLikelihoodFCN.h.

Member Function Documentation

◆ Dimension()

virtual unsigned int ROOT::Minuit2::FumiliFCNBase::Dimension ( )

inlinevirtualinherited

return number of function variable (parameters) , i.e.

function dimension

Definition at line 121 of file FumiliFCNBase.h.

◆ Elements()

std::vector< double > ROOT::Minuit2::FumiliStandardMaximumLikelihoodFCN::Elements ( std::vector< double > const & par ) const

overridevirtual

Evaluates the model function for the different measurement points and the Parameter values supplied.

Parameters

par	vector of Parameter values to feed to the model function.

Returns: A vector containing the model function evaluated for each measurement point.

Implements ROOT::Minuit2::FumiliMaximumLikelihoodFCN.

Definition at line 20 of file FumiliStandardMaximumLikelihoodFCN.cxx.

◆ ErrorDef()

virtual double ROOT::Minuit2::FCNBase::ErrorDef ( ) const

inlinevirtualinherited

Error definition of the function.

MINUIT defines Parameter errors as the change in Parameter Value required to change the function Value by up. Normally, for chisquared fits it is 1, and for negative log likelihood, its Value is 0.5. If the user wants instead the 2-sigma errors for chisquared fits, it becomes 4, as Chi2(x+n*sigma) = Chi2(x) + n*n.

Comment a little bit better with links!!!!!!!!!!!!!!!!!

Definition at line 70 of file FCNBase.h.

◆ EvaluateAll()

void ROOT::Minuit2::FumiliStandardMaximumLikelihoodFCN::EvaluateAll ( std::vector< double > const & par )

overridevirtual

Evaluate function Value, Gradient and Hessian using Fumili approximation, for values of parameters p The result is cached inside and is return from the FumiliFCNBase::Value , FumiliFCNBase::Gradient and FumiliFCNBase::Hessian methods.

Parameters

par	vector of parameters

Implements ROOT::Minuit2::FumiliFCNBase.

Definition at line 57 of file FumiliStandardMaximumLikelihoodFCN.cxx.

◆ G2()

virtual std::vector< double > ROOT::Minuit2::FCNBase::G2 ( std::vector< double > const & ) const

inlinevirtualinherited

Return the diagonal elements of the Hessian (second derivatives).

By default, returns an empty vector. Override this method if analytic second derivatives (per-parameter curvature) are available.

Parameters

v	Parameter vector.

Returns: Vector of second derivatives with respect to each parameter.

Reimplemented in ROOT::Minuit2::FCNAdapter.

Definition at line 116 of file FCNBase.h.

◆ GetMeasurement()

const std::vector< double > & ROOT::Minuit2::FumiliStandardMaximumLikelihoodFCN::GetMeasurement ( int Index ) const

overridevirtual

Accessor to the position of the measurement (x coordinate).

Parameters

Index Index of the measuerement the position of which to return.

Returns: the position of the measurement.

Implements ROOT::Minuit2::FumiliMaximumLikelihoodFCN.

Definition at line 45 of file FumiliStandardMaximumLikelihoodFCN.cxx.

◆ GetNumberOfMeasurements()

int ROOT::Minuit2::FumiliStandardMaximumLikelihoodFCN::GetNumberOfMeasurements ( ) const

overridevirtual

Accessor to the number of measurements used for calculating the maximum likelihood.

Returns: the number of measurements.

Implements ROOT::Minuit2::FumiliMaximumLikelihoodFCN.

Definition at line 51 of file FumiliStandardMaximumLikelihoodFCN.cxx.

◆ Gradient() [1/3]

std::vector< double > & ROOT::Minuit2::FumiliFCNBase::Gradient ( )

inlineprotectedinherited

Definition at line 138 of file FumiliFCNBase.h.

◆ Gradient() [2/3]

virtual const std::vector< double > & ROOT::Minuit2::FumiliFCNBase::Gradient ( ) const

inlinevirtualinherited

Return cached Value of function Gradient estimated previously using the FumiliFCNBase::EvaluateAll method.

Definition at line 97 of file FumiliFCNBase.h.

◆ Gradient() [3/3]

std::vector< double > ROOT::Minuit2::FumiliFCNBase::Gradient ( std::vector< double > const & ) const

inlineoverridevirtualinherited

Return the gradient vector of the function at the given parameter point.

By default, returns an empty vector (no analytic gradient provided). Override this method if an analytic gradient is available.

Parameters

v	Parameter vector.

Returns: Gradient vector with respect to the parameters.

Reimplemented from ROOT::Minuit2::FCNBase.

Definition at line 98 of file FumiliFCNBase.h.

◆ GradientWithPrevResult()

virtual std::vector< double > ROOT::Minuit2::FCNBase::GradientWithPrevResult	(	std::vector< double > const &	parameters,
		double *	,
		double *	,
		double *	) const

inlinevirtualinherited

Warning: Not meant to be overridden! This is a requirement for an internal optimization in RooFit that might go away with any refactoring.

Definition at line 99 of file FCNBase.h.

◆ gradParameterSpace()

virtual GradientParameterSpace ROOT::Minuit2::FCNBase::gradParameterSpace ( ) const

inlinevirtualinherited

Warning: Not meant to be overridden! This is a requirement for an internal optimization in RooFit that might go away with any refactoring.

Definition at line 107 of file FCNBase.h.

◆ HasG2()

virtual bool ROOT::Minuit2::FCNBase::HasG2 ( ) const

inlinevirtualinherited

Reimplemented in ROOT::Minuit2::FCNAdapter.

Definition at line 129 of file FCNBase.h.

◆ HasGradient()

bool ROOT::Minuit2::FumiliFCNBase::HasGradient ( ) const

inlineoverridevirtualinherited

Reimplemented from ROOT::Minuit2::FCNBase.

Definition at line 56 of file FumiliFCNBase.h.

◆ HasHessian()

virtual bool ROOT::Minuit2::FCNBase::HasHessian ( ) const

inlinevirtualinherited

Reimplemented in ROOT::Minuit2::FCNAdapter.

Definition at line 127 of file FCNBase.h.

◆ Hessian() [1/3]

std::vector< double > & ROOT::Minuit2::FumiliFCNBase::Hessian ( )

inlineprotectedinherited

Definition at line 140 of file FumiliFCNBase.h.

◆ Hessian() [2/3]

std::vector< double > ROOT::Minuit2::FumiliFCNBase::Hessian ( std::vector< double > const & ) const

inlineoverridevirtualinherited

Return Value of the i-th j-th element of the Hessian matrix estimated previously using the FumiliFCNBase::EvaluateAll method.

Parameters

row	row Index of the matrix
col	col Index of the matrix

Reimplemented from ROOT::Minuit2::FCNBase.

Definition at line 107 of file FumiliFCNBase.h.

◆ Hessian() [3/3]

virtual double ROOT::Minuit2::FumiliFCNBase::Hessian	(	unsigned int	row,
		unsigned int	col ) const

inlinevirtualinherited

Definition at line 108 of file FumiliFCNBase.h.

◆ InitAndReset()

virtual void ROOT::Minuit2::FumiliFCNBase::InitAndReset ( unsigned int npar )

inlineprotectedvirtualinherited

initialize and reset values of gradien and Hessian

Definition at line 128 of file FumiliFCNBase.h.

◆ ModelFunction()

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

inlineinherited

Returns the model function used for the data.

Returns: Returns a pointer to the model function.

Definition at line 69 of file FumiliMaximumLikelihoodFCN.h.

◆ operator()()

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

inlineoverridevirtualinherited

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

par	vector 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 127 of file FumiliMaximumLikelihoodFCN.h.

◆ SetErrorDef()

virtual void ROOT::Minuit2::FCNBase::SetErrorDef ( double )

inlinevirtualinherited

add interface to set dynamically a new error definition Re-implement this function if needed.

Reimplemented in ROOT::Minuit2::FCNAdapter, and ROOT::Minuit2::FumiliFCNAdapter< Function >.

Definition at line 84 of file FCNBase.h.

◆ SetFCNValue()

void ROOT::Minuit2::FumiliFCNBase::SetFCNValue ( double value )

inlineprotectedinherited

Definition at line 136 of file FumiliFCNBase.h.

◆ SetModelFunction()

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

inlineinherited

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

Parameters

modelFCN a reference to the model function.

Definition at line 59 of file FumiliMaximumLikelihoodFCN.h.

◆ Up()

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

inlineoverridevirtualinherited

!

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

Implements ROOT::Minuit2::FCNBase.

Definition at line 151 of file FumiliMaximumLikelihoodFCN.h.

◆ Value()

virtual double ROOT::Minuit2::FumiliFCNBase::Value ( ) const

inlinevirtualinherited

Return cached Value of objective function estimated previously using the FumiliFCNBase::EvaluateAll method.

Definition at line 91 of file FumiliFCNBase.h.

Member Data Documentation

◆ fGradient

std::vector<double> ROOT::Minuit2::FumiliFCNBase::fGradient

privateinherited

Definition at line 145 of file FumiliFCNBase.h.

◆ fHessian

std::vector<double> ROOT::Minuit2::FumiliFCNBase::fHessian

privateinherited

Definition at line 146 of file FumiliFCNBase.h.

◆ fModelFunction

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

privateinherited

Definition at line 155 of file FumiliMaximumLikelihoodFCN.h.

◆ fNumberOfParameters

unsigned int ROOT::Minuit2::FumiliFCNBase::fNumberOfParameters

privateinherited

Definition at line 143 of file FumiliFCNBase.h.

◆ fPositions

std::vector<std::vector<double> > ROOT::Minuit2::FumiliStandardMaximumLikelihoodFCN::fPositions

private

Definition at line 127 of file FumiliStandardMaximumLikelihoodFCN.h.

◆ fValue

double ROOT::Minuit2::FumiliFCNBase::fValue

privateinherited

Definition at line 144 of file FumiliFCNBase.h.

The documentation for this class was generated from the following files:

math/minuit2/inc/Minuit2/FumiliStandardMaximumLikelihoodFCN.h
math/minuit2/src/FumiliStandardMaximumLikelihoodFCN.cxx

Public Member Functions

Protected Member Functions

Private Attributes

Constructor & Destructor Documentation

◆ FumiliStandardMaximumLikelihoodFCN() [1/2]

◆ FumiliStandardMaximumLikelihoodFCN() [2/2]

Member Function Documentation

◆ Dimension()

◆ Elements()

◆ ErrorDef()

◆ EvaluateAll()

◆ G2()

◆ GetMeasurement()

◆ GetNumberOfMeasurements()

◆ Gradient() [1/3]

◆ Gradient() [2/3]

◆ Gradient() [3/3]

◆ GradientWithPrevResult()

◆ gradParameterSpace()

◆ HasG2()

◆ HasGradient()

◆ HasHessian()

◆ Hessian() [1/3]

◆ Hessian() [2/3]

◆ Hessian() [3/3]

◆ InitAndReset()

◆ ModelFunction()

◆ operator()()

◆ SetErrorDef()

◆ SetFCNValue()

◆ SetModelFunction()

◆ Up()

◆ Value()

Member Data Documentation

◆ fGradient

◆ fHessian

◆ fModelFunction

◆ fNumberOfParameters

◆ fPositions

◆ fValue