base class for function minimizers; user may give FCN or FCN with Gradient,
Parameter starting values and initial Error guess (sigma) (or "step size"),
or Parameter starting values and initial covariance matrix;
covariance matrix is stored in Upper triangular packed storage format,
e.g. the Elements in the array are arranged like
{a(0,0), a(0,1), a(1,1), a(0,2), a(1,2), a(2,2), ...},
the size is nrow*(nrow+1)/2 (see also MnUserCovariance.h);
virtual | ~FunctionMinimizer() |
ROOT::Minuit2::FunctionMinimizer | FunctionMinimizer() |
ROOT::Minuit2::FunctionMinimizer | FunctionMinimizer(const ROOT::Minuit2::FunctionMinimizer&) |
virtual ROOT::Minuit2::FunctionMinimum | Minimize(const ROOT::Minuit2::FCNBase&, const vector<double>& par, const vector<double>& err, unsigned int strategy, unsigned int maxfcn, double toler) const |
virtual ROOT::Minuit2::FunctionMinimum | Minimize(const ROOT::Minuit2::FCNGradientBase&, const vector<double>& par, const vector<double>& err, unsigned int strategy, unsigned int maxfcn, double toler) const |
virtual ROOT::Minuit2::FunctionMinimum | Minimize(const ROOT::Minuit2::FCNBase&, const vector<double>& par, unsigned int nrow, const vector<double>& cov, unsigned int strategy, unsigned int maxfcn, double toler) const |
virtual ROOT::Minuit2::FunctionMinimum | Minimize(const ROOT::Minuit2::FCNGradientBase&, const vector<double>& par, unsigned int nrow, const vector<double>& cov, unsigned int strategy, unsigned int maxfcn, double toler) const |
ROOT::Minuit2::FunctionMinimizer& | operator=(const ROOT::Minuit2::FunctionMinimizer&) |
starting values for parameters and errors
starting values for parameters and errors and FCN with Gradient
starting values for parameters and covariance matrix
starting values for parameters and covariance matrix and FCN with Gradient