class ROOT::Fit::LogLikelihoodFCN<ROOT::Math::IBaseFunctionMultiDim>: public ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>


   LogLikelihoodFCN class
   for likelihood fits

   it is template to distinguish gradient and non-gradient case

   @ingroup  FitMethodFunc

Function Members (Methods)

public:

virtual	~LogLikelihoodFCN<ROOT::Math::IBaseFunctionMultiDim>()
ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>	ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>(const ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>&)
ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>	ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>(int dim, int npoint)
virtual ROOT::Fit::LogLikelihoodFCN<ROOT::Math::IBaseFunctionMultiDim>::BaseFunction*	Clone() const
virtual const ROOT::Fit::UnBinData&	Data() const
virtual double	DataElement(const double* x, unsigned int i, double* g) const
virtual void	Gradient(const double* x, double* g) const
ROOT::Math::IBaseFunctionMultiDim	ROOT::Math::IBaseFunctionMultiDim::IBaseFunctionMultiDim()
ROOT::Math::IBaseFunctionMultiDim	ROOT::Math::IBaseFunctionMultiDim::IBaseFunctionMultiDim(const ROOT::Math::IBaseFunctionMultiDim&)
ROOT::Fit::LogLikelihoodFCN<ROOT::Math::IBaseFunctionMultiDim>	LogLikelihoodFCN<ROOT::Math::IBaseFunctionMultiDim>(const ROOT::Fit::UnBinData& data, const ROOT::Fit::LogLikelihoodFCN<ROOT::Math::IGradientFunctionMultiDim>::IModelFunction& func, int weight = 0, bool extended = false)
virtual const ROOT::Fit::LogLikelihoodFCN<ROOT::Math::IGradientFunctionMultiDim>::IModelFunction&	ModelFunction() const
virtual unsigned int	ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>::NCalls() const
virtual unsigned int	ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>::NDim() const
virtual unsigned int	NFitPoints() const
virtual unsigned int	ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>::NPoints() const
double	ROOT::Math::IBaseFunctionMultiDim::operator()(const double* x) const
virtual void	ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>::ResetNCalls()
virtual ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>::Type_t	Type() const
virtual void	ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>::UpdateNCalls() const
void	UseSumOfWeightSquare(bool on = true)

private:

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

Data Members

public:

static ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>::Type_t	ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>::kLeastSquare
static ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>::Type_t	ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>::kLogLikelihood
static ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>::Type_t	ROOT::Math::BasicFitMethodFunction<ROOT::Math::IBaseFunctionMultiDim>::kUndefined

private:

const ROOT::Fit::UnBinData&	fData
const ROOT::Fit::LogLikelihoodFCN<ROOT::Math::IGradientFunctionMultiDim>::IModelFunction&	fFunc
vector<double>	fGrad	for derivatives
bool	fIsExtended	flag for indicating if likelihood is extended
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 LogLikelihoodFCN(fData,fFunc,fWeight,fIsExtended); }

unsigned int NFitPoints() const

using BaseObjFunction::operator();
 effective points used in the fit

{ return fNEffPoints; }

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

 i-th likelihood contribution and its gradient

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

 need to be virtual to be instantited

void UseSumOfWeightSquare(bool on = true)

 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