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();.

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

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

double	ConfidenceLevel () const override
	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.

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

TestStatSampler *	GetTestStatSampler (void)
	Returns instance of TestStatSampler.

TClass *	IsA () const override

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

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

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

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

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

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

void	SetTestSize (double size) override
	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.

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

void	Streamer (TBuffer &) override

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

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

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

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

Static Public Member Functions
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

Static Public Member Functions inherited from RooStats::IntervalCalculator
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

Private Attributes
bool	fAdaptiveSampling
	controls use of adaptive sampling algorithm

double	fAdditionalNToysFactor
	give user ability to ask for more toys

ConfidenceBelt *	fConfBelt

bool	fCreateBelt
	controls use if ConfidenceBelt should be saved to a TFile

RooAbsData &	fData
	data set

double	fLeftSideFraction

ModelConfig &	fModel

RooAbsData *	fPointsToTest

bool	fSaveBeltToFile
	controls use if ConfidenceBelt should be saved to a TFile

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

TestStatSampler *	fTestStatSampler

#include <RooStats/NeymanConstruction.h>

Inheritance diagram for RooStats::NeymanConstruction:

[legend]

Constructor & Destructor Documentation

◆ NeymanConstruction()

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

NeymanConstruction();.

default constructor

Definition at line 79 of file NeymanConstruction.cxx.

◆ ~NeymanConstruction()

NeymanConstruction::~NeymanConstruction ( )

override

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 92 of file NeymanConstruction.h.

◆ Class()

static TClass * RooStats::NeymanConstruction::Class ( )

static

Returns: TClass describing this class

◆ Class_Name()

static const char * RooStats::NeymanConstruction::Class_Name ( )

static

Returns: Name of this class

◆ Class_Version()

static constexpr Version_t RooStats::NeymanConstruction::Class_Version ( )

inlinestaticconstexpr

Returns: Version of this class

Definition at line 123 of file NeymanConstruction.h.

◆ ConfidenceLevel()

double RooStats::NeymanConstruction::ConfidenceLevel ( ) const

inlineoverridevirtual

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 100 of file NeymanConstruction.h.

◆ DeclFileName()

static const char * RooStats::NeymanConstruction::DeclFileName ( )

inlinestatic

Returns: Name of the file containing the class declaration

Definition at line 123 of file NeymanConstruction.h.

◆ GetConfidenceBelt()

ConfidenceBelt * RooStats::NeymanConstruction::GetConfidenceBelt ( )

inline

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

Definition at line 86 of file NeymanConstruction.h.

◆ GetInterval()

PointSetInterval * NeymanConstruction::GetInterval ( ) const

overridevirtual

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 size);

Definition at line 104 of file NeymanConstruction.h.

◆ IsA()

TClass * RooStats::NeymanConstruction::IsA ( ) const

inlineoverridevirtual

Returns: TClass describing current object

Reimplemented from RooStats::IntervalCalculator.

Definition at line 123 of file NeymanConstruction.h.

◆ SaveBeltToFile()

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

inline

save the confidence belt to a file

Definition at line 95 of file NeymanConstruction.h.

◆ SetConfidenceLevel()

void RooStats::NeymanConstruction::SetConfidenceLevel ( double cl )

inlineoverridevirtual

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

Implements RooStats::IntervalCalculator.

Definition at line 83 of file NeymanConstruction.h.

◆ SetData()

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

inlineoverridevirtual

Set the DataSet.

Implements RooStats::IntervalCalculator.

Definition at line 78 of file NeymanConstruction.h.

◆ SetLeftSideTailFraction()

void RooStats::NeymanConstruction::SetLeftSideTailFraction ( double 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()

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

inlineoverridevirtual

Set ModelConfig.

Implements RooStats::IntervalCalculator.

Definition at line 75 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.

◆ SetTestSize()

void RooStats::NeymanConstruction::SetTestSize ( double size )

inlineoverridevirtual

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 81 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()

double RooStats::NeymanConstruction::Size ( ) const

inlineoverridevirtual

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.

◆ Streamer()

void RooStats::NeymanConstruction::Streamer ( TBuffer & )

overridevirtual

Reimplemented from RooStats::IntervalCalculator.

◆ StreamerNVirtual()

void RooStats::NeymanConstruction::StreamerNVirtual ( TBuffer & ClassDef_StreamerNVirtual_b )

inline

Definition at line 123 of file NeymanConstruction.h.

◆ UseAdaptiveSampling()

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

inline

adaptive sampling algorithm to speed up interval calculation

Definition at line 89 of file NeymanConstruction.h.

Member Data Documentation

◆ fAdaptiveSampling

bool RooStats::NeymanConstruction::fAdaptiveSampling

private

controls use of adaptive sampling algorithm

Definition at line 117 of file NeymanConstruction.h.

◆ fAdditionalNToysFactor

double RooStats::NeymanConstruction::fAdditionalNToysFactor

private

give user ability to ask for more toys

Definition at line 118 of file NeymanConstruction.h.

◆ fConfBelt

ConfidenceBelt* RooStats::NeymanConstruction::fConfBelt

private

Definition at line 116 of file NeymanConstruction.h.

◆ fCreateBelt

bool RooStats::NeymanConstruction::fCreateBelt

private

controls use if ConfidenceBelt should be saved to a TFile

Definition at line 120 of file NeymanConstruction.h.

◆ fData

RooAbsData& RooStats::NeymanConstruction::fData

private

data set

Definition at line 110 of file NeymanConstruction.h.

◆ fLeftSideFraction

double RooStats::NeymanConstruction::fLeftSideFraction

private

Definition at line 115 of file NeymanConstruction.h.

◆ fModel

ModelConfig& RooStats::NeymanConstruction::fModel

private

Definition at line 111 of file NeymanConstruction.h.

◆ fPointsToTest

RooAbsData* RooStats::NeymanConstruction::fPointsToTest

private

Definition at line 114 of file NeymanConstruction.h.

◆ fSaveBeltToFile

bool RooStats::NeymanConstruction::fSaveBeltToFile

private

controls use if ConfidenceBelt should be saved to a TFile

Definition at line 119 of file NeymanConstruction.h.

◆ fSize

double RooStats::NeymanConstruction::fSize

private

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

Definition at line 109 of file NeymanConstruction.h.

◆ fTestStatSampler

TestStatSampler* RooStats::NeymanConstruction::fTestStatSampler

private

Definition at line 113 of file NeymanConstruction.h.

Libraries for RooStats::NeymanConstruction:

[legend]

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

Static Public Member Functions

Private Attributes

Constructor & Destructor Documentation

◆ NeymanConstruction()

◆ ~NeymanConstruction()

Member Function Documentation

◆ AdditionalNToysFactor()

◆ Class()

◆ Class_Name()

◆ Class_Version()

◆ ConfidenceLevel()

◆ CreateConfBelt()

◆ DeclFileName()

◆ GetConfidenceBelt()

◆ GetInterval()

◆ GetTestStatSampler()

◆ IsA()

◆ SaveBeltToFile()

◆ SetConfidenceLevel()

◆ SetData()

◆ SetLeftSideTailFraction()

◆ SetModel()

◆ SetParameterPointsToTest()

◆ SetTestSize()

◆ SetTestStatSampler()

◆ Size()

◆ Streamer()

◆ StreamerNVirtual()

◆ UseAdaptiveSampling()

Member Data Documentation

◆ fAdaptiveSampling

◆ fAdditionalNToysFactor

◆ fConfBelt

◆ fCreateBelt

◆ fData

◆ fLeftSideFraction

◆ fModel

◆ fPointsToTest

◆ fSaveBeltToFile

◆ fSize

◆ fTestStatSampler