class RooStats::BayesianCalculator: public RooStats::IntervalCalculator, public TNamed


   BayesianCalculator is a concrete implementation of IntervalCalculator.
   It computes the posterior probability density functions using the
   numerical (or analytical integration) for integrating the product of the
   likelihood and prior functions (Bayes theorem).
   The class works only for problems with only one parameter of interest,
   the posterior is a one-dimensional function
   The class computes via  GetInterval() the central Bayesian credible intervals

   Note: when nuisance parameters are present a multi-dimensional integration is
   needed. In some cases, when the integration must be performed numerically, evaluating the posterior or
   getting the interval (calling GetInterval) can result in long execution time.
   In these case using the MCMCCalculator could be more convenient

Function Members (Methods)

public:

virtual	~BayesianCalculator()
void	TObject::AbstractMethod(const char* method) const
virtual void	TObject::AppendPad(Option_t* option = "")
RooStats::BayesianCalculator	BayesianCalculator()
RooStats::BayesianCalculator	BayesianCalculator(const RooStats::BayesianCalculator&)
RooStats::BayesianCalculator	BayesianCalculator(RooAbsData& data, RooStats::ModelConfig& model)
RooStats::BayesianCalculator	BayesianCalculator(RooAbsData& data, RooAbsPdf& pdf, const RooArgSet& POI, RooAbsPdf& priorPOI, const RooArgSet* nuisanceParameters = 0)
virtual void	TObject::Browse(TBrowser* b)
static TClass*	Class()
virtual const char*	TObject::ClassName() const
virtual void	TNamed::Clear(Option_t* option = "")
virtual TObject*	TNamed::Clone(const char* newname = "") const
virtual Int_t	TNamed::Compare(const TObject* obj) const
virtual Double_t	ConfidenceLevel() const
virtual void	TNamed::Copy(TObject& named) const
virtual void	TObject::Delete(Option_t* option = "")MENU
virtual Int_t	TObject::DistancetoPrimitive(Int_t px, Int_t py)
virtual void	TObject::Draw(Option_t* option = "")
virtual void	TObject::DrawClass() constMENU
virtual TObject*	TObject::DrawClone(Option_t* option = "") constMENU
virtual void	TObject::Dump() constMENU
virtual void	TObject::Error(const char* method, const char* msgfmt) const
virtual void	TObject::Execute(const char* method, const char* params, Int_t* error = 0)
virtual void	TObject::Execute(TMethod* method, TObjArray* params, Int_t* error = 0)
virtual void	TObject::ExecuteEvent(Int_t event, Int_t px, Int_t py)
virtual void	TObject::Fatal(const char* method, const char* msgfmt) const
virtual void	TNamed::FillBuffer(char*& buffer)
virtual TObject*	TObject::FindObject(const char* name) const
virtual TObject*	TObject::FindObject(const TObject* obj) const
virtual Option_t*	TObject::GetDrawOption() const
static Long_t	TObject::GetDtorOnly()
virtual const char*	TObject::GetIconName() const
virtual RooStats::SimpleInterval*	GetInterval() const
virtual const char*	TNamed::GetName() const
virtual char*	TObject::GetObjectInfo(Int_t px, Int_t py) const
static Bool_t	TObject::GetObjectStat()
virtual Option_t*	TObject::GetOption() const
RooAbsPdf*	GetPosteriorPdf() const
RooPlot*	GetPosteriorPlot() const
virtual const char*	TNamed::GetTitle() const
virtual UInt_t	TObject::GetUniqueID() const
virtual Bool_t	TObject::HandleTimer(TTimer* timer)
virtual ULong_t	TNamed::Hash() const
virtual void	TObject::Info(const char* method, const char* msgfmt) const
virtual Bool_t	TObject::InheritsFrom(const char* classname) const
virtual Bool_t	TObject::InheritsFrom(const TClass* cl) const
virtual void	TObject::Inspect() constMENU
void	TObject::InvertBit(UInt_t f)
virtual TClass*	IsA() const
virtual Bool_t	TObject::IsEqual(const TObject* obj) const
virtual Bool_t	TObject::IsFolder() const
Bool_t	TObject::IsOnHeap() const
virtual Bool_t	TNamed::IsSortable() const
Bool_t	TObject::IsZombie() const
virtual void	TNamed::ls(Option_t* option = "") const
void	TObject::MayNotUse(const char* method) const
virtual Bool_t	TObject::Notify()
static void	TObject::operator delete(void* ptr)
static void	TObject::operator delete(void* ptr, void* vp)
static void	TObject::operator delete[](void* ptr)
static void	TObject::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::BayesianCalculator&	operator=(const RooStats::BayesianCalculator&)
virtual void	TObject::Paint(Option_t* option = "")
virtual void	TObject::Pop()
virtual void	TNamed::Print(Option_t* option = "") const
virtual Int_t	TObject::Read(const char* name)
virtual void	TObject::RecursiveRemove(TObject* obj)
void	TObject::ResetBit(UInt_t f)
virtual void	TObject::SaveAs(const char* filename = "", Option_t* option = "") constMENU
virtual void	TObject::SavePrimitive(basic_ostream<char,char_traits<char> >& out, Option_t* option = "")
void	TObject::SetBit(UInt_t f)
void	TObject::SetBit(UInt_t f, Bool_t set)
virtual void	SetConfidenceLevel(Double_t cl)
virtual void	SetData(RooAbsData& data)
virtual void	TObject::SetDrawOption(Option_t* option = "")MENU
static void	TObject::SetDtorOnly(void* obj)
virtual void	SetModel(const RooStats::ModelConfig& model)
virtual void	TNamed::SetName(const char* name)MENU
virtual void	TNamed::SetNameTitle(const char* name, const char* title)
static void	TObject::SetObjectStat(Bool_t stat)
virtual void	SetTestSize(Double_t size)
virtual void	TNamed::SetTitle(const char* title = "")MENU
virtual void	TObject::SetUniqueID(UInt_t uid)
virtual void	ShowMembers(TMemberInspector& insp, char* parent)
virtual Double_t	Size() const
virtual Int_t	TNamed::Sizeof() const
virtual void	Streamer(TBuffer& b)
void	StreamerNVirtual(TBuffer& b)
virtual void	TObject::SysError(const char* method, const char* msgfmt) const
Bool_t	TObject::TestBit(UInt_t f) const
Int_t	TObject::TestBits(UInt_t f) const
virtual void	TObject::UseCurrentStyle()
virtual void	TObject::Warning(const char* method, const char* msgfmt) const
virtual Int_t	TObject::Write(const char* name = 0, Int_t option = 0, Int_t bufsize = 0)
virtual Int_t	TObject::Write(const char* name = 0, Int_t option = 0, Int_t bufsize = 0) const

protected:

void	ClearAll() const
virtual void	TObject::DoError(int level, const char* location, const char* fmt, va_list va) const
void	TObject::MakeZombie()

private:

RooArgSet*

GetMode(RooArgSet* parameters) const

Data Members

public:

enum TObject::EStatusBits {	kCanDelete
	kMustCleanup
	kObjInCanvas
	kIsReferenced
	kHasUUID
	kCannotPick
	kNoContextMenu
	kInvalidObject
};
enum TObject::[unnamed] {	kIsOnHeap
	kNotDeleted
	kZombie
	kBitMask
	kSingleKey
	kOverwrite
	kWriteDelete
};

protected:

TString	TNamed::fName	object identifier
TString	TNamed::fTitle	object title

private:

RooAbsData*	fData
RooAbsReal*	fIntegratedLikelihood
RooStats::SimpleInterval*	fInterval	cached pointer to resulting interval
RooAbsReal*	fLikelihood
RooAbsReal*	fLogLike
RooArgSet	fNuisanceParameters
RooArgSet	fPOI
RooAbsPdf*	fPdf
RooAbsPdf*	fPosteriorPdf
RooAbsPdf*	fPriorPOI
RooAbsPdf*	fProductPdf
double	fSize	size used for getting the interval

Class Charts

Inheritance Inherited Members Includes Libraries

Function documentation

BayesianCalculator()

 default constructor. Need to call the Setter methods afterwards

BayesianCalculator( /* const char* name, const char* title, */ RooAbsData& data, RooAbsPdf& pdf, const RooArgSet& POI, RooAbsPdf& priorPOI, const RooArgSet* nuisanceParameters )

TNamed( TString(name), TString(title) ),
 constructor from data set, model pdf, set with the parameter of interest
 (must contain only one parameter for the moment) and prior pdf
 Optionally an additional set of parameters can be specified (nuisance parameters)
 which will be integrated (marginalized) when creating the posterior pdf.
 A default size of 0.05 is used (for 95% CL interval)

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

 Same constructor but from data and a ModelConfig describing the model pdf and the prior, the parameter
 of interest and the nuisance parameters

~BayesianCalculator()

 destructor cleaning all managed objects

void ClearAll() const

 clear cached pdf objects (posterior pdf, Likelihood, NLL, etc.)

void SetModel(const RooStats::ModelConfig& model)

 set the model configuration

RooArgSet* GetMode(RooArgSet* parameters) const

 return the mode (not yet implemented) but can be easly obtained from
  GetPosteriorPdf()->asTF(poi)->GetMaximumX();

RooAbsPdf* GetPosteriorPdf() const

 get the posterior pdf as a RooAbsPdf
 the posterior is obtained from the product of the likelihood function and the
 prior pdf which is then intergated in the nuisance parameters (if existing).
 A prior function for the nuisance can be specified either in the prior pdf object
 or in the model itself. If no prior nuisance is specified, but prior parameters are then
 the integration is performed assuming a flat prior for the nuisance parameters.

RooPlot* GetPosteriorPlot() const

 return a RooPlot with the posterior PDF and the credibility region

SimpleInterval* GetInterval() const

 returns a SimpleInterval with the lower/upper limit on
 the scanned variable (the parameter of interest specified in the constructor).
 The returned interval is a central interval with the confidence level specified
 previously in SetConfidenceLevel (default is 0.95).
 NOTE1: for finding only an upper/lower limit of 95 % the CL must be set to 0.90
 NOTE2: The method can result very slow when nuisance parameters are present due to
        the time needed for performing multi-dimensional numerical integration.
        In these case using the MCMCCalculator could be more convenient.

BayesianCalculator()

 constructor

void SetData(RooAbsData& data)

{ fData = &data; }

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 SetConfidenceLevel(Double_t cl)

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

{ SetTestSize(1.-cl); }

Double_t Size() const

 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; }