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class RooStats::NeymanConstruction: public RooStats::IntervalCalculator, public TNamed

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 constrution 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.

Function Members (Methods)

voidTObject::AbstractMethod(const char* method) const
virtual voidTObject::AppendPad(Option_t* option = "")
virtual voidTObject::Browse(TBrowser* b)
static TClass*Class()
virtual const char*TObject::ClassName() const
virtual voidTNamed::Clear(Option_t* option = "")
virtual TObject*TNamed::Clone(const char* newname = "") const
virtual Int_tTNamed::Compare(const TObject* obj) const
virtual Double_tConfidenceLevel() const
virtual voidTNamed::Copy(TObject& named) const
voidCreateConfBelt(bool flag = true)
virtual voidTObject::Delete(Option_t* option = "")MENU
virtual Int_tTObject::DistancetoPrimitive(Int_t px, Int_t py)
virtual voidTObject::Draw(Option_t* option = "")
virtual voidTObject::DrawClass() constMENU
virtual TObject*TObject::DrawClone(Option_t* option = "") constMENU
virtual voidTObject::Dump() constMENU
virtual voidTObject::Error(const char* method, const char* msgfmt) const
virtual voidTObject::Execute(const char* method, const char* params, Int_t* error = 0)
virtual voidTObject::Execute(TMethod* method, TObjArray* params, Int_t* error = 0)
virtual voidTObject::ExecuteEvent(Int_t event, Int_t px, Int_t py)
virtual voidTObject::Fatal(const char* method, const char* msgfmt) const
virtual voidTNamed::FillBuffer(char*& buffer)
virtual TObject*TObject::FindObject(const char* name) const
virtual TObject*TObject::FindObject(const TObject* obj) const
virtual TList*GenSamplingDistribution(const char* asciiFilePat = 0) const
virtual Option_t*TObject::GetDrawOption() const
static Long_tTObject::GetDtorOnly()
virtual const char*TObject::GetIconName() const
virtual RooStats::ConfInterval*GetInterval() const
virtual RooStats::ConfInterval*GetInterval(const char* asciiFilePat) const
virtual RooStats::ConfInterval*GetIntervalUsingList() const
virtual const char*TNamed::GetName() const
virtual char*TObject::GetObjectInfo(Int_t px, Int_t py) const
static Bool_tTObject::GetObjectStat()
virtual Option_t*TObject::GetOption() const
virtual const char*TNamed::GetTitle() const
virtual UInt_tTObject::GetUniqueID() const
virtual Bool_tTObject::HandleTimer(TTimer* timer)
virtual ULong_tTNamed::Hash() const
virtual voidTObject::Info(const char* method, const char* msgfmt) const
virtual Bool_tTObject::InheritsFrom(const char* classname) const
virtual Bool_tTObject::InheritsFrom(const TClass* cl) const
virtual voidTObject::Inspect() constMENU
voidTObject::InvertBit(UInt_t f)
virtual TClass*IsA() const
virtual Bool_tTObject::IsEqual(const TObject* obj) const
virtual Bool_tTObject::IsFolder() const
Bool_tTObject::IsOnHeap() const
virtual Bool_tTNamed::IsSortable() const
Bool_tTObject::IsZombie() const
virtual voidTNamed::ls(Option_t* option = "") const
voidTObject::MayNotUse(const char* method) const
RooStats::NeymanConstructionNeymanConstruction(const RooStats::NeymanConstruction&)
virtual Bool_tTObject::Notify()
static voidTObject::operator delete(void* ptr)
static voidTObject::operator delete(void* ptr, void* vp)
static voidTObject::operator delete[](void* ptr)
static voidTObject::operator delete[](void* ptr, void* vp)
void*TObject::operator new(size_t sz)
void*TObject::operator new(size_t sz, void* vp)
void*TObject::operator new[](size_t sz)
void*TObject::operator new[](size_t sz, void* vp)
RooStats::NeymanConstruction&operator=(const RooStats::NeymanConstruction&)
virtual voidTObject::Paint(Option_t* option = "")
virtual voidTObject::Pop()
virtual voidTNamed::Print(Option_t* option = "") const
virtual Int_tTObject::Read(const char* name)
virtual voidTObject::RecursiveRemove(TObject* obj)
voidTObject::ResetBit(UInt_t f)
virtual RooStats::ConfInterval*Run(TList* SamplingList) const
virtual voidTObject::SaveAs(const char* filename = "", Option_t* option = "") constMENU
voidSaveBeltToFile(bool flag = true)
virtual voidTObject::SavePrimitive(basic_ostream<char,char_traits<char> >& out, Option_t* option = "")
voidTObject::SetBit(UInt_t f)
voidTObject::SetBit(UInt_t f, Bool_t set)
virtual voidSetConfidenceLevel(Double_t cl)
virtual voidSetData(RooAbsData& data)
virtual voidTObject::SetDrawOption(Option_t* option = "")MENU
static voidTObject::SetDtorOnly(void* obj)
voidSetLeftSideTailFraction(Double_t leftSideFraction = 0.)
virtual voidSetModel(const RooStats::ModelConfig&)
virtual voidTNamed::SetName(const char* name)MENU
virtual voidTNamed::SetNameTitle(const char* name, const char* title)
virtual voidSetNuisanceParameters(const RooArgSet& set)
static voidTObject::SetObjectStat(Bool_t stat)
voidSetParameterPointsToTest(RooAbsData& pointsToTest)
virtual voidSetParameters(const RooArgSet& set)
virtual voidSetPdf(RooAbsPdf& pdf)
virtual voidSetTestSize(Double_t size)
voidSetTestStatSampler(RooStats::TestStatSampler& distCreator)
virtual voidTNamed::SetTitle(const char* title = "")MENU
virtual voidTObject::SetUniqueID(UInt_t uid)
virtual voidShowMembers(TMemberInspector& insp, char* parent)
virtual Double_tSize() const
virtual Int_tTNamed::Sizeof() const
virtual voidStreamer(TBuffer& b)
voidStreamerNVirtual(TBuffer& b)
virtual voidTObject::SysError(const char* method, const char* msgfmt) const
Bool_tTObject::TestBit(UInt_t f) const
Int_tTObject::TestBits(UInt_t f) const
voidUseAdaptiveSampling(bool flag = true)
virtual voidTObject::UseCurrentStyle()
virtual voidTObject::Warning(const char* method, const char* msgfmt) const
virtual Int_tTObject::Write(const char* name = 0, Int_t option = 0, Int_t bufsize = 0)
virtual Int_tTObject::Write(const char* name = 0, Int_t option = 0, Int_t bufsize = 0) const
virtual voidTObject::DoError(int level, const char* location, const char* fmt, va_list va) const

Data Members

TStringTNamed::fNameobject identifier
TStringTNamed::fTitleobject title
boolfAdaptiveSamplingcontrols use of adaptive sampling algorithm
boolfCreateBeltcontrols use if ConfidenceBelt should be saved to a TFile
RooAbsData*fDatadata set
RooArgSetfNuisParamsRooArgSet specifying nuisance parameters for interval
RooArgSetfPOIRooArgSet specifying parameters of interest for interval
RooAbsPdf*fPdfcommon PDF
boolfSaveBeltToFilecontrols use if ConfidenceBelt should be saved to a TFile
Double_tfSizesize of the test (eg. specified rate of Type I error)

Class Charts

Inheritance Inherited Members Includes Libraries
Class Charts

Function documentation

 default constructor
   fWS = new RooWorkspace();
   fOwnsWorkspace = true;
   fDataName = "";
   fPdfName = "";
void SetModel(const RooStats::ModelConfig& )
 set the model
 default constructor
  if(fOwnsWorkspace && fWS) delete fWS;
  if(fConfBelt) delete fConfBelt;
ConfInterval* GetInterval() const
 Main interface to get a RooStats::ConfInterval.
 It constructs a RooStats::SetInterval.
TList* GenSamplingDistribution(const char* asciiFilePat = 0) const
This method generates the sampling distribution for each point of the study. If a file path
is provided, the distribution is saved in a root file. Returns the list of the distributions
for each point.
ConfInterval* GetIntervalUsingList() const
 Main interface to get a RooStats::ConfInterval.
 It constructs a RooStats::PointSetInterval.
ConfInterval* GetInterval(const char* asciiFilePat) const
This method returns a confidence interval exactly like GetInterval(), but
instead of generating the sampling disribution (long computation) it takes
the distribution from the file provided
ConfInterval* Run(TList* SamplingList) const
Main method to perform the interval calculation
void SetTestStatSampler(RooStats::TestStatSampler& distCreator)
 in addition to interface we also need:
 Set the TestStatSampler (eg. ToyMC or FFT, includes choice of TestStatistic)
{fTestStatSampler = &distCreator;}
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(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 SetData(RooAbsData& data)
 Set the DataSet
{ fData = &data; }
void SetPdf(RooAbsPdf& pdf)
 Set the Pdf, add to the the workspace if not already there
{ fPdf = &pdf; }
void SetParameters(const RooArgSet& set)
 specify the parameters of interest in the interval
{ fPOI.removeAll(); fPOI.add(set); }
void SetNuisanceParameters(const RooArgSet& set)
 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()
{return fConfBelt;}
void UseAdaptiveSampling(bool flag = true)
void SaveBeltToFile(bool flag = true)
void CreateConfBelt(bool flag = true)
{fCreateBelt = flag;}