ROOT::Minuit2::FumiliMaximumLikelihoodFCN Class Reference

Description

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

Todo:

Insert a nice latex formula...

Definition at line 51 of file FumiliMaximumLikelihoodFCN.h.

Inheritance diagram for ROOT::Minuit2::FumiliMaximumLikelihoodFCN:

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Public Member Functions
	FumiliMaximumLikelihoodFCN ()
virtual	~FumiliMaximumLikelihoodFCN ()
virtual unsigned int	Dimension ()
virtual std::vector< double >	Elements (const std::vector< double > &par) const =0
virtual double	ErrorDef () const
virtual void	EvaluateAll (const std::vector< double > &par)=0
virtual const std::vector< double > &	GetMeasurement (int Index) const =0
virtual int	GetNumberOfMeasurements () const =0
virtual const std::vector< double > &	Gradient () const
virtual double	Hessian (unsigned int row, unsigned int col) const
const ParametricFunction *	ModelFunction () const
double	operator() (const std::vector< double > &par) const
virtual void	SetErrorDef (double)
void	SetModelFunction (const ParametricFunction &modelFCN)
virtual double	Up () const
virtual double	Value () const

Protected Member Functions
std::vector< double > &	Gradient ()
std::vector< double > &	Hessian ()
virtual void	InitAndReset (unsigned int npar)
void	SetFCNValue (double value)

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

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

Dimension()

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

inlinevirtualinherited

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

Definition at line 132 of file FumiliFCNBase.h.

{ return fNumberOfParameters; }

References ROOT::Minuit2::FumiliFCNBase::fNumberOfParameters.

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.

Referenced by operator()().

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 93 of file FCNBase.h.

{return Up();}

References ROOT::Minuit2::FCNBase::Up().

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EvaluateAll()

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

pure virtualinherited

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

Parameters

par	vector of parameters

Implemented in ROOT::Minuit2::FumiliFCNAdapter< Function >, ROOT::Minuit2::FumiliStandardMaximumLikelihoodFCN, and ROOT::Minuit2::FumiliStandardChi2FCN.

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

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.

Gradient() [1/2]

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

inlineprotectedinherited

Definition at line 149 of file FumiliFCNBase.h.

{ return fGradient; }

References ROOT::Minuit2::FumiliFCNBase::fGradient.

Gradient() [2/2]

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 112 of file FumiliFCNBase.h.

{ return fGradient; }

References ROOT::Minuit2::FumiliFCNBase::fGradient.

Hessian() [1/2]

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

inlineprotectedinherited

Definition at line 151 of file FumiliFCNBase.h.

{ return fHessian; }

References ROOT::Minuit2::FumiliFCNBase::fHessian.

Hessian() [2/2]

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

inlinevirtualinherited

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

Definition at line 120 of file FumiliFCNBase.h.

                                                                    {
      assert( row < fGradient.size() && col < fGradient.size() );
      if(row > col)
         return fHessian[col+row*(row+1)/2];
      else
         return fHessian[row+col*(col+1)/2];
   }

References ROOT::Minuit2::FumiliFCNBase::fGradient, and ROOT::Minuit2::FumiliFCNBase::fHessian.

InitAndReset()

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

inlineprotectedvirtualinherited

initialize and reset values of gradien and Hessian

Definition at line 140 of file FumiliFCNBase.h.

                                                {
      fNumberOfParameters = npar;
      fGradient = std::vector<double>(npar);
      fHessian = std::vector<double>(static_cast<int>( 0.5*npar*(npar+1) ));
   }

References ROOT::Minuit2::FumiliFCNBase::fGradient, ROOT::Minuit2::FumiliFCNBase::fHessian, and ROOT::Minuit2::FumiliFCNBase::fNumberOfParameters.

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.

{ return fModelFunction; }

References fModelFunction.

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

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 144 of file FumiliMaximumLikelihoodFCN.h.

                                                        {
 
     double sumoflogs = 0.0;
     std::vector<double> vecElements =  Elements(par);
     unsigned int vecElementsSize = vecElements.size();
 
     for (unsigned int i = 0; i < vecElementsSize; ++i) {
        double tmp = vecElements[i];
        //for max likelihood probability have to be positive
        assert(tmp >= 0);
        sumoflogs -= ROOT::Math::Util::EvalLog(tmp);
        //std::cout << " i " << tmp << " lik " << sumoflogs << std::endl;
     }
 
 
     return sumoflogs;
  }

References Elements(), and ROOT::Math::Util::EvalLog().

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

Definition at line 114 of file FCNBase.h.

{};

SetFCNValue()

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

inlineprotectedinherited

Definition at line 147 of file FumiliFCNBase.h.

{ fValue = value; }

References ROOT::Minuit2::FumiliFCNBase::fValue.

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

modelFunction

a reference to the model function.

Definition at line 68 of file FumiliMaximumLikelihoodFCN.h.

{ fModelFunction = &modelFCN; }

References fModelFunction.

Referenced by ROOT::Minuit2::FumiliStandardMaximumLikelihoodFCN::FumiliStandardMaximumLikelihoodFCN().

Up()

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

inlinevirtual

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

Implements ROOT::Minuit2::FCNBase.

Definition at line 170 of file FumiliMaximumLikelihoodFCN.h.

{ return 0.5; }

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 106 of file FumiliFCNBase.h.

{ return fValue; }

References ROOT::Minuit2::FumiliFCNBase::fValue.

Member Data Documentation

fGradient

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

privateinherited

Definition at line 160 of file FumiliFCNBase.h.

Referenced by ROOT::Minuit2::FumiliFCNBase::Gradient(), ROOT::Minuit2::FumiliFCNBase::Hessian(), and ROOT::Minuit2::FumiliFCNBase::InitAndReset().

fHessian

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

privateinherited

Definition at line 161 of file FumiliFCNBase.h.

Referenced by ROOT::Minuit2::FumiliFCNBase::Hessian(), and ROOT::Minuit2::FumiliFCNBase::InitAndReset().

fModelFunction

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

private

Definition at line 175 of file FumiliMaximumLikelihoodFCN.h.

Referenced by ModelFunction(), and SetModelFunction().

fNumberOfParameters

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

privateinherited

Definition at line 158 of file FumiliFCNBase.h.

Referenced by ROOT::Minuit2::FumiliFCNBase::Dimension(), and ROOT::Minuit2::FumiliFCNBase::InitAndReset().

fValue

double ROOT::Minuit2::FumiliFCNBase::fValue

privateinherited

Definition at line 159 of file FumiliFCNBase.h.

Referenced by ROOT::Minuit2::FumiliFCNBase::SetFCNValue(), and ROOT::Minuit2::FumiliFCNBase::Value().

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

• /home/build/builds/o5h8MZZm/0/mlz/bornagain/Fit/3rdparty/RootMinimizers/Minuit2/FumiliMaximumLikelihoodFCN.h