The FeldmanCousins class (like the Feldman-Cousins technique) is essentially a specific configuration of the more general NeymanConstruction. It is a concrete implementation of the IntervalCalculator interface that, which uses the NeymanConstruction in a particular way. As the name suggests, it returns a ConfidenceInterval. In particular, it produces a RooStats::PointSetInterval, which is a concrete implementation of the ConfInterval interface.
The Neyman Construction is not a uniquely defined statistical technique, it requires that one specify an ordering rule or ordering principle, which is usually incoded by choosing a specific test statistic and limits of integration (corresponding to upper/lower/central limits). As a result, this class must be configured with the corresponding information before it can produce an interval.
In the case of the Feldman-Cousins approach, the ordering principle is the likelihood ratio -- motivated by the Neyman-Pearson lemma. When nuisance parameters are involved, the profile likelihood ratio is the natural generalization. One may either choose to perform the construction over the full space of the nuisance parameters, or restrict the nusiance parameters to their conditional MLE (eg. profiled values).
void | CreateParameterPoints() const |
void | CreateTestStatSampler() const |
Bool_t | fAdaptiveSampling | controls use of adaptive sampling algorithm |
Double_t | fAdditionalNToysFactor | give user ability to ask for more toys |
RooStats::ConfidenceBelt* | fConfBelt | |
Bool_t | fCreateBelt | controls use if ConfidenceBelt should be saved to a TFile |
RooAbsData& | fData | data set |
Bool_t | fDoProfileConstruction | instead of full construction over nuisance parametrs, do profile |
Bool_t | fFluctuateData | tell ToyMCSampler to fluctuate number of entries in dataset |
RooStats::ModelConfig& | fModel | |
Int_t | fNbins | number of samples per variable |
RooAbsData* | fPointsToTest | points to perform the construction |
Bool_t | fSaveBeltToFile | controls use if ConfidenceBelt should be saved to a TFile |
Double_t | fSize | size of the test (eg. specified rate of Type I error) |
RooStats::ToyMCSampler* | fTestStatSampler | the test statistic sampler |
specify the Test Statistic and create a ToyMC test statistic sampler
specify the parameter points to perform the construction. allow ability to profile on some nuisance paramters
Main interface to get a RooStats::ConfInterval. It constructs a RooStats::PointSetInterval.
specify the nuisance parameters (eg. the rest of the parameters)
set the size of the test (rate of Type I error) ( Eg. 0.05 for a 95% Confidence Interval)
{fSize = size;}
set the confidence level for the interval (eg. 0.95 for a 95% Confidence Interval)
{fSize = 1.-cl;}