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A++ » ROOSTATS » RooStats::NeymanConstruction

class RooStats::NeymanConstruction: public RooStats::IntervalCalculator

Function Members (Methods)

public:

virtual	~NeymanConstruction()
void	AdditionalNToysFactor(double fact)
static TClass*	Class()
virtual Double_t	ConfidenceLevel() const
void	CreateConfBelt(bool flag = true)
RooStats::ConfidenceBelt*	GetConfidenceBelt()
virtual RooStats::PointSetInterval*	GetInterval() const
RooStats::TestStatSampler*	GetTestStatSampler()
RooStats::IntervalCalculator	RooStats::IntervalCalculator::IntervalCalculator()
RooStats::IntervalCalculator	RooStats::IntervalCalculator::IntervalCalculator(const RooStats::IntervalCalculator&)
virtual TClass*	IsA() const
RooStats::NeymanConstruction	NeymanConstruction(const RooStats::NeymanConstruction&)
RooStats::NeymanConstruction	NeymanConstruction(RooAbsData& data, RooStats::ModelConfig& model)
RooStats::NeymanConstruction&	operator=(const RooStats::NeymanConstruction&)
void	SaveBeltToFile(bool flag = true)
virtual void	SetConfidenceLevel(Double_t cl)
virtual void	SetData(RooAbsData& data)
void	SetLeftSideTailFraction(Double_t leftSideFraction = 0.)
virtual void	SetModel(const RooStats::ModelConfig& model)
virtual void	SetNuisanceParameters(const RooArgSet&)
void	SetParameterPointsToTest(RooAbsData& pointsToTest)
virtual void	SetParameters(const RooArgSet&)
virtual void	SetPdf(RooAbsPdf&)
virtual void	SetTestSize(Double_t size)
void	SetTestStatSampler(RooStats::TestStatSampler& sampler)
virtual void	ShowMembers(TMemberInspector& insp) const
virtual Double_t	Size() const
virtual void	Streamer(TBuffer&)
void	StreamerNVirtual(TBuffer& ClassDef_StreamerNVirtual_b)
void	UseAdaptiveSampling(bool flag = true)

Data Members

private:

bool	fAdaptiveSampling	controls use of adaptive sampling algorithm
Double_t	fAdditionalNToysFactor	give user ability to ask for more toys
RooStats::ConfidenceBelt*	fConfBelt
bool	fCreateBelt	controls use if ConfidenceBelt should be saved to a TFile
RooAbsData&	fData	/ data set
Double_t	fLeftSideFraction
RooStats::ModelConfig&	fModel
RooAbsData*	fPointsToTest
bool	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::TestStatSampler*	fTestStatSampler

Class Charts

Inheritance Chart:

RooStats::IntervalCalculator

←

RooStats::NeymanConstruction

Function documentation

NeymanConstruction(RooAbsData& data, RooStats::ModelConfig& model)

     NeymanConstruction();

virtual ~NeymanConstruction()

PointSetInterval* GetInterval() const

 Main interface to get a ConfInterval (will be a PointSetInterval)

void SetTestStatSampler(RooStats::TestStatSampler& sampler)

 in addition to interface we also need:
 Set the TestStatSampler (eg. ToyMC or FFT, includes choice of TestStatistic)

{fTestStatSampler = &sampler;}

void SetLeftSideTailFraction(Double_t leftSideFraction = 0.)

 fLeftSideTailFraction*fSize defines lower edge of acceptance region.
 Unified limits use 0, central limits use 0.5,
 for upper/lower limits it is 0/1 depends on sign of test statistic w.r.t. parameter

{fLeftSideFraction = leftSideFraction;}

void SetParameterPointsToTest(RooAbsData& pointsToTest)

 User-defined set of points to test

Double_t Size() const

 This class can make regularly spaced scans based on range stored in RooRealVars.
 Choose number of steps for a rastor scan (common for each dimension)
      void SetNumSteps(Int_t);
 This class can make regularly spaced scans based on range stored in RooRealVars.
 Choose number of steps for a rastor scan (specific for each dimension)
      void SetNumSteps(std::map<RooAbsArg, Int_t>)
 Get the size of the test (eg. rate of Type I error)

{return fSize;}

Double_t ConfidenceLevel() const

 Get the Confidence level for the test

{return 1.-fSize;}

void SetModel(const RooStats::ModelConfig& model)

 Set ModelConfig

{fModel = model;}

void SetData(RooAbsData& data)

 Set the DataSet

{ fData = data; }

void SetPdf(RooAbsPdf& )

 Set the Pdf, add to the the workspace if not already there

void SetParameters(const RooArgSet& )

 specify the parameters of interest in the interval

void SetNuisanceParameters(const RooArgSet& )

 specify the nuisance parameters (eg. the rest of the parameters)

void SetTestSize(Double_t size)

 set the size of the test (rate of Type I error) ( Eg. 0.05 for a 95% Confidence Interval)

{fSize = size;}

void SetConfidenceLevel(Double_t cl)

 set the confidence level for the interval (eg. 0.95 for a 95% Confidence Interval)

{fSize = 1.-cl;}

ConfidenceBelt* GetConfidenceBelt()

 get confidence belt

{return fConfBelt;}

void UseAdaptiveSampling(bool flag = true)

 adaptive sampling algorithm to speed up interval caculation

{fAdaptiveSampling=flag;}

void AdditionalNToysFactor(double fact)

 give user ability to ask for more toys

{fAdditionalNToysFactor = fact;}

void SaveBeltToFile(bool flag = true)

 save teh confidence belt to a file

void CreateConfBelt(bool flag = true)

 should create confidence belt

{fCreateBelt = flag;}

TestStatSampler* GetTestStatSampler(void)

 Returns instance of TestStatSampler. Use to change properties of
 TestStatSampler, e.g. GetTestStatSampler.SetTestSize(Double_t size);

{ return fTestStatSampler; }