class containg the result of the fit and all the related information (fitted parameter values, error, covariance matrix and minimizer result information) Contains a pointer also to the fitted (model) function, modified with the fit parameter values. When the fit is valid, it is constructed from a Minimizer and a model function pointer @ingroup FitMain
| ~FitResult() | |
| double | Chi2() const |
| double | Correlation(unsigned int i, unsigned int j) const |
| double | CovMatrix(unsigned int i, unsigned int j) const |
| double | Edm() const |
| double | Error(unsigned int i) const |
| const vector<double>& | Errors() const |
| ROOT::Fit::FitResult | FitResult() |
| ROOT::Fit::FitResult | FitResult(const ROOT::Fit::FitResult&) |
| ROOT::Fit::FitResult | FitResult(ROOT::Math::Minimizer& min, const ROOT::Fit::FitConfig& fconfig, const ROOT::Fit::FitResult::IModelFunction* f, bool isValid, unsigned int sizeOfData = 0, bool binFit = true, const ROOT::Math::IMultiGenFunction* chi2func = 0, bool minosErr = false, unsigned int ncalls = 0) |
| const ROOT::Fit::FitResult::IModelFunction* | FittedFunction() const |
| void | GetConfidenceIntervals(const ROOT::Fit::BinData& data, double* ci, double cl = 0.95) const |
| void | GetConfidenceIntervals(unsigned int n, unsigned int stride1, unsigned int stride2, const double* x, double* ci, double cl = 0.95) const |
| string | GetParameterName(unsigned int ipar) const |
| double | GlobalCC(unsigned int i) const |
| int | Index(const string& name) const |
| bool | IsEmpty() const |
| bool | IsParameterBound(unsigned int ipar) const |
| bool | IsParameterFixed(unsigned int ipar) const |
| bool | IsValid() const |
| double | LowerError(unsigned int i) const |
| double | MinFcnValue() const |
| const string& | MinimizerType() const |
| unsigned int | NCalls() const |
| unsigned int | Ndf() const |
| unsigned int | NFreeParameters() const |
| bool | NormalizedErrors() |
| void | NormalizeErrors() |
| unsigned int | NTotalParameters() const |
| ROOT::Fit::FitResult& | operator=(const ROOT::Fit::FitResult& rhs) |
| const vector<double>& | Parameters() const |
| void | Print(ostream& os, bool covmat = false) const |
| void | PrintCovMatrix(ostream& os) const |
| double | Prob() const |
| int | Status() const |
| double | UpperError(unsigned int i) const |
| double | Value(unsigned int i) const |
| ROOT::Fit::FitResult::IModelFunction* | ModelFunction() |
| void | SetModelFunction(ROOT::Fit::FitResult::IModelFunction* func) |
| vector<unsigned int> | fBoundParams | list of limited parameters |
| double | fChi2 | fit chi2 value (different than fval in case of chi2 fits) |
| vector<double> | fCovMatrix | covariance matrix (size is npar*(npar+1)/2) where npar is total parameters |
| double | fEdm | expected distance from mimimum |
| vector<double> | fErrors | errors |
| ROOT::Fit::FitResult::IModelFunction* | fFitFunc | model function resulting from the fit. It is given by Fitter but it is managed by FitResult |
| vector<unsigned int> | fFixedParams | list of fixed parameters |
| vector<double> | fGlobalCC | global Correlation coefficient |
| string | fMinimType | string indicating type of minimizer |
| vector<std::pair<double,double> > | fMinosErrors | vector contains the two Minos errors |
| unsigned int | fNCalls | number of function calls |
| unsigned int | fNFree | number of fit free parameters (total parameters are in size of parameter vector) |
| unsigned int | fNdf | number of degree of freedom |
| bool | fNormalized | flag for indicating is errors are normalized |
| vector<std::string> | fParNames | parameter names (only with FCN only fites, when fFitFunc=0) |
| vector<double> | fParams | parameter values. Size is total number of parameters |
| int | fStatus | minimizer status code |
| double | fVal | minimum function value |
| bool | fValid | flag for indicating valid fit |
Construct from a Minimizer instance
minimization quantities minimizer type
{ return fMinimType; }True if a fit result does not exist (even invalid) with parameter values
{ return (fParams.size() == 0); }Return value of the objective function (chi2 or likelihood) used in the fit
{ return fVal; }fitting quantities Return pointer to model (fit) function with fitted parameter values.
{ return fFitFunc; }
get confidence intervals for an array of n points x.
stride1 indicates the stride in the coordinate space while stride2 the stride in dimension space.
For 1-dim points : stride1=1, stride2=1
for multi-dim points arranged as (x0,x1,...,xN,y0,....yN) stride1=1 stride2=n
for multi-dim points arraged as (x0,y0,..,x1,y1,...,xN,yN,..) stride1=ndim, stride2=1
the confidence interval are returned in the array ci
cl is the desired confidedence interval value
evaluate confidence interval for the point specified in the passed data sets
the confidence interval are returned in the array ci
cl is the desired confidence interval value
get confidence level given an array of x data points print the result and optionaly covariance matrix and correlations