ROOT   6.21/01 Reference Guide
RooStats::NeymanConstruction Class Reference

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 35 of file NeymanConstruction.h.

## Public Member Functions

NeymanConstruction (RooAbsData &data, ModelConfig &model)
NeymanConstruction();. More...

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

give user ability to ask for more toys More...

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

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

ConfidenceBeltGetConfidenceBelt ()
get confidence belt More...

virtual PointSetIntervalGetInterval () const
Main interface to get a ConfInterval (will be a PointSetInterval) More...

TestStatSamplerGetTestStatSampler (void)
Returns instance of TestStatSampler. More...

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

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

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

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

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

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

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

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

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

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) More...

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

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

adaptive sampling algorithm to speed up interval calculation More...

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

## Private Attributes

ConfidenceBeltfConfBelt

bool fCreateBelt

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

Double_t fLeftSideFraction

ModelConfigfModel
data set More...

RooAbsDatafPointsToTest

bool fSaveBeltToFile

Double_t fSize

TestStatSamplerfTestStatSampler

#include <RooStats/NeymanConstruction.h>

Inheritance diagram for RooStats::NeymanConstruction:
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## ◆ NeymanConstruction()

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

default constructor

Definition at line 80 of file NeymanConstruction.cxx.

## ◆ ~NeymanConstruction()

 NeymanConstruction::~NeymanConstruction ( )
virtual

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

Definition at line 105 of file NeymanConstruction.cxx.

## Member Function Documentation

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

give user ability to ask for more toys

Definition at line 106 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 71 of file NeymanConstruction.h.

## ◆ CreateConfBelt()

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

should create confidence belt

Definition at line 114 of file NeymanConstruction.h.

## ◆ GetConfidenceBelt()

 ConfidenceBelt* RooStats::NeymanConstruction::GetConfidenceBelt ( )
inline

get confidence belt

Definition at line 100 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 112 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 118 of file NeymanConstruction.h.

## ◆ SaveBeltToFile()

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

save the confidence belt to a file

Definition at line 109 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 97 of file NeymanConstruction.h.

## ◆ SetData()

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

Set the DataSet.

Implements RooStats::IntervalCalculator.

Definition at line 77 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 53 of file NeymanConstruction.h.

## ◆ SetModel()

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

Set ModelConfig.

Implements RooStats::IntervalCalculator.

Definition at line 74 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 90 of file NeymanConstruction.h.

## ◆ SetParameterPointsToTest()

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

User-defined set of points to test.

Definition at line 56 of file NeymanConstruction.h.

## ◆ SetParameters()

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

specify the parameters of interest in the interval

Definition at line 85 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 80 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 95 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 49 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 68 of file NeymanConstruction.h.

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

adaptive sampling algorithm to speed up interval calculation

Definition at line 103 of file NeymanConstruction.h.

## Member Data Documentation

private

Definition at line 136 of file NeymanConstruction.h.

private

Definition at line 137 of file NeymanConstruction.h.

## ◆ fConfBelt

 ConfidenceBelt* RooStats::NeymanConstruction::fConfBelt
private

Definition at line 135 of file NeymanConstruction.h.

## ◆ fCreateBelt

 bool RooStats::NeymanConstruction::fCreateBelt
private

Definition at line 139 of file NeymanConstruction.h.

## ◆ fData

 RooAbsData& RooStats::NeymanConstruction::fData
private

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

Definition at line 124 of file NeymanConstruction.h.

## ◆ fLeftSideFraction

 Double_t RooStats::NeymanConstruction::fLeftSideFraction
private

Definition at line 134 of file NeymanConstruction.h.

## ◆ fModel

 ModelConfig& RooStats::NeymanConstruction::fModel
private

data set

Definition at line 125 of file NeymanConstruction.h.

## ◆ fPointsToTest

 RooAbsData* RooStats::NeymanConstruction::fPointsToTest
private

Definition at line 133 of file NeymanConstruction.h.

## ◆ fSaveBeltToFile

 bool RooStats::NeymanConstruction::fSaveBeltToFile
private

Definition at line 138 of file NeymanConstruction.h.

## ◆ fSize

 Double_t RooStats::NeymanConstruction::fSize
private

Definition at line 123 of file NeymanConstruction.h.

## ◆ fTestStatSampler

 TestStatSampler* RooStats::NeymanConstruction::fTestStatSampler
private

Definition at line 132 of file NeymanConstruction.h.

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