class ROOT::Fit::PoissonLikelihoodFCN<ROOT::Math::IGradientFunctionMultiDim>: public ROOT::Math::BasicFitMethodFunction<ROOT::Math::IGradientFunctionMultiDim>


   class evaluating the log likelihood
   for binned Poisson likelihood fits
   it is template to distinguish gradient and non-gradient case

   @ingroup  FitMethodFunc

This class is also known as (typedefs to this class)

ROOT::Fit::PoissonLLGradFunction, ROOT::Fit::PoissonLikelihoodFCN<ROOT::Math::IMultiGradFunction>

Function Members (Methods)

public:

virtual	~PoissonLikelihoodFCN<ROOT::Math::IGradientFunctionMultiDim>()
virtual ROOT::Fit::PoissonLikelihoodFCN<ROOT::Math::IGradientFunctionMultiDim>::BaseFunction*	Clone() const
virtual const ROOT::Fit::BinData&	Data() const
virtual double	DataElement(const double* x, unsigned int i, double* g) const
double	ROOT::Math::IGradientMultiDim::Derivative(const double* x, unsigned int icoord = 0) const
virtual void	ROOT::Math::IGradientFunctionMultiDim::FdF(const double* x, double& f, double* df) const
virtual void	Gradient(const double* x, double* g) const
bool	IsWeighted() const
virtual const ROOT::Fit::PoissonLikelihoodFCN<ROOT::Math::IGradientFunctionMultiDim>::IModelFunction&	ModelFunction() const
virtual unsigned int	ROOT::Math::BasicFitMethodFunction<ROOT::Math::IGradientFunctionMultiDim>::NCalls() const
virtual unsigned int	ROOT::Math::BasicFitMethodFunction<ROOT::Math::IGradientFunctionMultiDim>::NDim() const
virtual unsigned int	NFitPoints() const
virtual unsigned int	ROOT::Math::BasicFitMethodFunction<ROOT::Math::IGradientFunctionMultiDim>::NPoints() const
double	ROOT::Math::IBaseFunctionMultiDim::operator()(const double* x) const
ROOT::Fit::PoissonLikelihoodFCN<ROOT::Math::IGradientFunctionMultiDim>	PoissonLikelihoodFCN<ROOT::Math::IGradientFunctionMultiDim>(const ROOT::Fit::BinData& data, const ROOT::Fit::PoissonLikelihoodFCN<ROOT::Math::IGradientFunctionMultiDim>::IModelFunction& func, int weight = 0, bool extended = true)
virtual void	ROOT::Math::BasicFitMethodFunction<ROOT::Math::IGradientFunctionMultiDim>::ResetNCalls()
virtual ROOT::Math::BasicFitMethodFunction<ROOT::Math::IGradientFunctionMultiDim>::Type_t	Type() const
virtual void	ROOT::Math::BasicFitMethodFunction<ROOT::Math::IGradientFunctionMultiDim>::UpdateNCalls() const
void	UseSumOfWeights()
void	UseSumOfWeightSquare()

private:

virtual double	DoDerivative(const double* x, unsigned int icoord) const
virtual double	DoEval(const double* x) const
ROOT::Fit::PoissonLikelihoodFCN<ROOT::Math::IGradientFunctionMultiDim>&	operator=(const ROOT::Fit::PoissonLikelihoodFCN<ROOT::Math::IGradientFunctionMultiDim>&)
ROOT::Fit::PoissonLikelihoodFCN<ROOT::Math::IGradientFunctionMultiDim>	PoissonLikelihoodFCN<ROOT::Math::IGradientFunctionMultiDim>(const ROOT::Fit::PoissonLikelihoodFCN<ROOT::Math::IGradientFunctionMultiDim>&)

Data Members

public:

enum ROOT::Math::BasicFitMethodFunction::Type_t {	kUndefined
	kLeastSquare
	kLogLikelihood
};

private:

const ROOT::Fit::BinData&	fData
const ROOT::Fit::PoissonLikelihoodFCN<ROOT::Math::IGradientFunctionMultiDim>::IModelFunction&	fFunc
vector<double>	fGrad	for derivatives
bool	fIsExtended	flag to indicate if is extended (when false is a Multinomial lieklihood), default is true
unsigned int	fNEffPoints	number of effective points used in the fit
int	fWeight	flag to indicate if needs to evaluate using weight or weight squared (default weight = 0)

Class Charts

Inheritance Inherited Members Includes Libraries

Function documentation

BaseFunction * Clone() const

 clone the function (need to return Base for Windows)

{ return new PoissonLikelihoodFCN(fData,fFunc,fWeight,fIsExtended); }

unsigned int NFitPoints() const

 effective points used in the fit

{ return fNEffPoints; }

double DataElement(const double* x, unsigned int i, double* g) const

 i-th likelihood element and its gradient

void Gradient(const double* x, double* g) const

 evaluate gradient

bool IsWeighted() const

{ return (fWeight != 0); }

void UseSumOfWeights()

 Use the weights in evaluating the likelihood

void UseSumOfWeightSquare()

 Use sum of the weight squared in evaluating the likelihood
 (this is needed for calculating the errors)

double DoEval(const double* x) const

      Evaluation of the  function (required by interface)

double DoDerivative(const double* x, unsigned int icoord) const

 for derivatives