NeymanConstruction is a concrete implementation of the NeymanConstruction interface that, as the name suggests, performs a NeymanConstruction.

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. Common configurations, such as the Feldman-Cousins approach, can be enforced by other light weight classes.

The Neyman Construction considers every point in the parameter space independently, no assumptions are made that the interval is connected or of a particular shape. As a result, the PointSetInterval class is used to represent the result. The user indicate which points in the parameter space to perform the construction by providing a PointSetInterval instance with the desired points.

This class is fairly light weight, because the choice of parameter points to be considered is factorized and so is the creation of the sampling distribution of the test statistic (which is done by a concrete class implementing the DistributionCreator interface). As a result, this class basically just drives the construction by:

using a DistributionCreator to create the SamplingDistribution of a user- defined test statistic for each parameter point of interest,
defining the acceptance region in the data by finding the thresholds on the test statistic such that the integral of the sampling distribution is of the appropriate size and consistent with the limits of integration (eg. upper/lower/central limits),
and finally updating the PointSetInterval based on whether the value of the test statistic evaluated on the data are in the acceptance region.

Definition at line 36 of file NeymanConstruction.h.

Public Member Functions
	NeymanConstruction (RooAbsData &data, ModelConfig &model)
	NeymanConstruction();.

virtual	~NeymanConstruction ()
	default constructor if(fOwnsWorkspace && fWS) delete fWS; if(fConfBelt) delete fConfBelt;

void	AdditionalNToysFactor (double fact)
	give user ability to ask for more toys

virtual Double_t	ConfidenceLevel () const
	Get the Confidence level for the test.

void	CreateConfBelt (bool flag=true)
	should create confidence belt

ConfidenceBelt *	GetConfidenceBelt ()
	Get confidence belt. This requires that CreateConfBelt() has been called.

virtual PointSetInterval *	GetInterval () const
	Main interface to get a ConfInterval (will be a PointSetInterval)

TestStatSampler *	GetTestStatSampler (void)
	Returns instance of TestStatSampler.

void	SaveBeltToFile (bool flag=true)
	save the confidence belt to a file

virtual void	SetConfidenceLevel (Double_t cl)
	set the confidence level for the interval (eg. 0.95 for a 95% Confidence Interval)

virtual void	SetData (RooAbsData &data)
	Set the DataSet.

void	SetLeftSideTailFraction (Double_t leftSideFraction=0.)
	fLeftSideTailFraction*fSize defines lower edge of acceptance region.

virtual void	SetModel (const ModelConfig &model)
	Set ModelConfig.

virtual void	SetNuisanceParameters (const RooArgSet &)
	specify the nuisance parameters (eg. the rest of the parameters)

void	SetParameterPointsToTest (RooAbsData &pointsToTest)
	User-defined set of points to test.

virtual void	SetParameters (const RooArgSet &)
	specify the parameters of interest in the interval

virtual void	SetPdf (RooAbsPdf &)
	Set the Pdf, add to the the workspace if not already there.

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

void	SetTestStatSampler (TestStatSampler &sampler)
	in addition to interface we also need: Set the TestStatSampler (eg.

virtual Double_t	Size () const
	This class can make regularly spaced scans based on range stored in RooRealVars.

void	UseAdaptiveSampling (bool flag=true)
	adaptive sampling algorithm to speed up interval calculation

Public Member Functions inherited from RooStats::IntervalCalculator
virtual	~IntervalCalculator ()

Private Attributes
bool	fAdaptiveSampling

Double_t	fAdditionalNToysFactor

ConfidenceBelt *	fConfBelt

bool	fCreateBelt

RooAbsData &	fData
	size of the test (eg. specified rate of Type I error)

Double_t	fLeftSideFraction

ModelConfig &	fModel
	data set

RooAbsData *	fPointsToTest

bool	fSaveBeltToFile

Double_t	fSize

TestStatSampler *	fTestStatSampler

#include <RooStats/NeymanConstruction.h>

Inheritance diagram for RooStats::NeymanConstruction:

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Constructor & Destructor Documentation

◆ NeymanConstruction()

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

NeymanConstruction();.

default constructor

Definition at line 79 of file NeymanConstruction.cxx.

◆ ~NeymanConstruction()

NeymanConstruction::~NeymanConstruction ( )

virtual

default constructor if(fOwnsWorkspace && fWS) delete fWS; if(fConfBelt) delete fConfBelt;

Definition at line 104 of file NeymanConstruction.cxx.

Member Function Documentation

◆ AdditionalNToysFactor()

void RooStats::NeymanConstruction::AdditionalNToysFactor ( double fact )

inline

give user ability to ask for more toys

Definition at line 107 of file NeymanConstruction.h.

◆ ConfidenceLevel()

virtual Double_t RooStats::NeymanConstruction::ConfidenceLevel ( ) const

inlinevirtual

Get the Confidence level for the test.

Implements RooStats::IntervalCalculator.

Definition at line 72 of file NeymanConstruction.h.

◆ CreateConfBelt()

void RooStats::NeymanConstruction::CreateConfBelt ( bool flag = true )

inline

should create confidence belt

Definition at line 115 of file NeymanConstruction.h.

◆ GetConfidenceBelt()

ConfidenceBelt * RooStats::NeymanConstruction::GetConfidenceBelt ( )

inline

Get confidence belt. This requires that CreateConfBelt() has been called.

Definition at line 101 of file NeymanConstruction.h.

◆ GetInterval()

PointSetInterval * NeymanConstruction::GetInterval ( ) const

virtual

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

Main interface to get a RooStats::ConfInterval.

It constructs a RooStats::SetInterval.

Implements RooStats::IntervalCalculator.

Definition at line 111 of file NeymanConstruction.cxx.

◆ GetTestStatSampler()

TestStatSampler * RooStats::NeymanConstruction::GetTestStatSampler ( void )

inline

Returns instance of TestStatSampler.

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

Definition at line 119 of file NeymanConstruction.h.

◆ SaveBeltToFile()

void RooStats::NeymanConstruction::SaveBeltToFile ( bool flag = true )

inline

save the confidence belt to a file

Definition at line 110 of file NeymanConstruction.h.

◆ SetConfidenceLevel()

virtual void RooStats::NeymanConstruction::SetConfidenceLevel ( Double_t cl )

inlinevirtual

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

Implements RooStats::IntervalCalculator.

Definition at line 98 of file NeymanConstruction.h.

◆ SetData()

virtual void RooStats::NeymanConstruction::SetData ( RooAbsData & data )

inlinevirtual

Set the DataSet.

Implements RooStats::IntervalCalculator.

Definition at line 78 of file NeymanConstruction.h.

◆ SetLeftSideTailFraction()

void RooStats::NeymanConstruction::SetLeftSideTailFraction ( Double_t leftSideFraction = 0. )

inline

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

Definition at line 54 of file NeymanConstruction.h.

◆ SetModel()

virtual void RooStats::NeymanConstruction::SetModel ( const ModelConfig & model )

inlinevirtual

Set ModelConfig.

Implements RooStats::IntervalCalculator.

Definition at line 75 of file NeymanConstruction.h.

◆ SetNuisanceParameters()

virtual void RooStats::NeymanConstruction::SetNuisanceParameters ( const RooArgSet & )

inlinevirtual

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

Definition at line 91 of file NeymanConstruction.h.

◆ SetParameterPointsToTest()

void RooStats::NeymanConstruction::SetParameterPointsToTest ( RooAbsData & pointsToTest )

inline

User-defined set of points to test.

Definition at line 57 of file NeymanConstruction.h.

◆ SetParameters()

virtual void RooStats::NeymanConstruction::SetParameters ( const RooArgSet & )

inlinevirtual

specify the parameters of interest in the interval

Definition at line 86 of file NeymanConstruction.h.

◆ SetPdf()

virtual void RooStats::NeymanConstruction::SetPdf ( RooAbsPdf & )

inlinevirtual

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

Definition at line 81 of file NeymanConstruction.h.

◆ SetTestSize()

virtual void RooStats::NeymanConstruction::SetTestSize ( Double_t size )

inlinevirtual

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

Implements RooStats::IntervalCalculator.

Definition at line 96 of file NeymanConstruction.h.

◆ SetTestStatSampler()

void RooStats::NeymanConstruction::SetTestStatSampler ( TestStatSampler & sampler )

inline

in addition to interface we also need: Set the TestStatSampler (eg.

ToyMC or FFT, includes choice of TestStatistic)

Definition at line 50 of file NeymanConstruction.h.

◆ Size()

virtual Double_t RooStats::NeymanConstruction::Size ( ) const

inlinevirtual

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)

Implements RooStats::IntervalCalculator.

Definition at line 69 of file NeymanConstruction.h.

◆ UseAdaptiveSampling()

void RooStats::NeymanConstruction::UseAdaptiveSampling ( bool flag = true )

inline

adaptive sampling algorithm to speed up interval calculation

Definition at line 104 of file NeymanConstruction.h.

Member Data Documentation

◆ fAdaptiveSampling

bool RooStats::NeymanConstruction::fAdaptiveSampling

private

Definition at line 137 of file NeymanConstruction.h.

◆ fAdditionalNToysFactor

Double_t RooStats::NeymanConstruction::fAdditionalNToysFactor

private

Definition at line 138 of file NeymanConstruction.h.

◆ fConfBelt

ConfidenceBelt* RooStats::NeymanConstruction::fConfBelt

private

Definition at line 136 of file NeymanConstruction.h.

◆ fCreateBelt

bool RooStats::NeymanConstruction::fCreateBelt

private

Definition at line 140 of file NeymanConstruction.h.

◆ fData

RooAbsData& RooStats::NeymanConstruction::fData

private

size of the test (eg. specified rate of Type I error)

Definition at line 125 of file NeymanConstruction.h.

◆ fLeftSideFraction

Double_t RooStats::NeymanConstruction::fLeftSideFraction

private

Definition at line 135 of file NeymanConstruction.h.

◆ fModel

ModelConfig& RooStats::NeymanConstruction::fModel

private

data set

Definition at line 126 of file NeymanConstruction.h.

◆ fPointsToTest

RooAbsData* RooStats::NeymanConstruction::fPointsToTest

private

Definition at line 134 of file NeymanConstruction.h.

◆ fSaveBeltToFile

bool RooStats::NeymanConstruction::fSaveBeltToFile

private

Definition at line 139 of file NeymanConstruction.h.

◆ fSize

Double_t RooStats::NeymanConstruction::fSize

private

Definition at line 124 of file NeymanConstruction.h.

◆ fTestStatSampler

TestStatSampler* RooStats::NeymanConstruction::fTestStatSampler

private

Definition at line 133 of file NeymanConstruction.h.

Libraries for RooStats::NeymanConstruction:

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The documentation for this class was generated from the following files:

roofit/roostats/inc/RooStats/NeymanConstruction.h
roofit/roostats/src/NeymanConstruction.cxx

Public Member Functions

Private Attributes

Constructor & Destructor Documentation

◆ NeymanConstruction()

◆ ~NeymanConstruction()

Member Function Documentation

◆ AdditionalNToysFactor()

◆ ConfidenceLevel()

◆ CreateConfBelt()

◆ GetConfidenceBelt()

◆ GetInterval()

◆ GetTestStatSampler()

◆ SaveBeltToFile()

◆ SetConfidenceLevel()

◆ SetData()

◆ SetLeftSideTailFraction()

◆ SetModel()

◆ SetNuisanceParameters()

◆ SetParameterPointsToTest()

◆ SetParameters()

◆ SetPdf()

◆ SetTestSize()

◆ SetTestStatSampler()

◆ Size()

◆ UseAdaptiveSampling()

Member Data Documentation

◆ fAdaptiveSampling

◆ fAdditionalNToysFactor

◆ fConfBelt

◆ fCreateBelt

◆ fData

◆ fLeftSideFraction

◆ fModel

◆ fPointsToTest

◆ fSaveBeltToFile

◆ fSize

◆ fTestStatSampler