class evaluating the log likelihood for binned Poisson likelihood fits it is template to distinguish gradient and non-gradient case @ingroup FitMethodFunc
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>&) |
enum ROOT::Math::BasicFitMethodFunction | kUndefined | |
kLeastSquare | ||
kLogLikelihood | ||
}; |
const ROOT::Fit::BinData& | fData | |
const ROOT::Fit::PoissonLikelihoodFCN<ROOT::Math::IGradientFunctionMultiDim>::IModelFunction& | fFunc | |
vector<double> | fGrad | for derivatives |
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 |
i-th likelihood element and its gradient
Use sum of the weight squared in evaluating the likelihood (this is needed for calculating the errors)