~MnHesse() | |
ROOT::Minuit2::MnHesse | MnHesse() |
ROOT::Minuit2::MnHesse | MnHesse(unsigned int stra) |
ROOT::Minuit2::MnHesse | MnHesse(const ROOT::Minuit2::MnStrategy& stra) |
ROOT::Minuit2::MnHesse | MnHesse(const ROOT::Minuit2::MnHesse&) |
unsigned int | Ncycles() const |
ROOT::Minuit2::MnUserParameterState | operator()(const ROOT::Minuit2::FCNBase&, const ROOT::Minuit2::MnUserParameters&, unsigned int maxcalls = 0) const |
ROOT::Minuit2::MnUserParameterState | operator()(const ROOT::Minuit2::FCNBase&, const ROOT::Minuit2::MnUserParameterState&, unsigned int maxcalls = 0) const |
void | operator()(const ROOT::Minuit2::FCNBase&, ROOT::Minuit2::FunctionMinimum&, unsigned int maxcalls = 0) const |
ROOT::Minuit2::MnUserParameterState | operator()(const ROOT::Minuit2::FCNBase&, const vector<double>&, const vector<double>&, unsigned int maxcalls = 0) const |
ROOT::Minuit2::MnUserParameterState | operator()(const ROOT::Minuit2::FCNBase&, const vector<double>&, const ROOT::Minuit2::MnUserCovariance&, unsigned int maxcalls = 0) const |
ROOT::Minuit2::MnUserParameterState | operator()(const ROOT::Minuit2::FCNBase&, const ROOT::Minuit2::MnUserParameters&, const ROOT::Minuit2::MnUserCovariance&, unsigned int maxcalls = 0) const |
ROOT::Minuit2::MinimumState | operator()(const ROOT::Minuit2::MnFcn&, const ROOT::Minuit2::MinimumState&, const ROOT::Minuit2::MnUserTransformation&, unsigned int maxcalls = 0) const |
ROOT::Minuit2::MnUserParameterState | operator()(const ROOT::Minuit2::FCNBase&, const vector<double>&, unsigned int nrow, const vector<double>&, unsigned int maxcalls = 0) const |
ROOT::Minuit2::MnHesse& | operator=(const ROOT::Minuit2::MnHesse&) |
double | TolerG2() const |
double | Tolerstp() const |
ROOT::Minuit2::MnStrategy | fStrategy |
low-level API FCN + parameters + errors
FCN + parameters + covariance
FCN + parameters + MnUserCovariance
high-level API FCN + MnUserParameters
FCN + MnUserParameters + MnUserCovariance
FCN + MnUserParameterState
API to use MnHesse after minimization when function mimimum is avalilable, otherwise information on the last state will be lost. (It would be needed to re-call the gradient and spend extra useless function calls) The Function Minimum is updated (modified) by adding the Hesse results as last state of minimization
internal interface