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ROOT » ROOFIT » ROOSTATS » RooStats::ProfileLikelihoodTestStat

class RooStats::ProfileLikelihoodTestStat: public RooStats::TestStatistic

ProfileLikelihoodTestStat is an implementation of the TestStatistic interface that calculates the profile likelihood ratio at a particular parameter point given a dataset. It does not constitute a statistical test, for that one may either use:

the ProfileLikelihoodCalculator that relies on asymptotic properties of the Profile Likelihood Ratio
the Neyman Construction classes with this class as a test statistic
the Hybrid Calculator class with this class as a test statistic

Function Members (Methods)

public:

virtual	~ProfileLikelihoodTestStat()
static TClass*	Class()
virtual void	EnableDetailedOutput(bool e = true, bool withErrorsAndPulls = false)
virtual Double_t	Evaluate(RooAbsData& data, RooArgSet& paramsOfInterest)
virtual Double_t	EvaluateProfileLikelihood(int type, RooAbsData& data, RooArgSet& paramsOfInterest)
virtual const RooArgSet*	GetDetailedOutput() const
virtual RooAbsPdf*	GetPdf() const
virtual const TString	GetVarName() const
virtual TClass*	IsA() const
bool	IsOneSidedDiscovery() const
bool	IsTwoSided() const
RooStats::TestStatistic&	RooStats::TestStatistic::operator=(const RooStats::TestStatistic&)
RooStats::ProfileLikelihoodTestStat	ProfileLikelihoodTestStat()
RooStats::ProfileLikelihoodTestStat	ProfileLikelihoodTestStat(RooAbsPdf& pdf)
RooStats::ProfileLikelihoodTestStat	ProfileLikelihoodTestStat(const RooStats::ProfileLikelihoodTestStat&)
virtual bool	RooStats::TestStatistic::PValueIsRightTail() const
static void	SetAlwaysReuseNLL(Bool_t flag)
virtual void	SetConditionalObservables(const RooArgSet& set)
void	SetLOffset(Bool_t flag = kTRUE)
void	SetMinimizer(const char* minimizer)
void	SetOneSided(Bool_t flag = true)
void	SetOneSidedDiscovery(Bool_t flag = true)
void	SetPrintLevel(Int_t printlevel)
void	SetReuseNLL(Bool_t flag)
void	SetSigned(Bool_t flag = true)
void	SetStrategy(Int_t strategy)
void	SetTolerance(double tol)
virtual void	SetVarName(const char* name)
virtual void	ShowMembers(TMemberInspector&)
virtual void	Streamer(TBuffer&)
void	StreamerNVirtual(TBuffer& ClassDef_StreamerNVirtual_b)

private:

RooFitResult*

GetMinNLL()

Data Members

public:

enum LimitType {	twoSided
	oneSided
	oneSidedDiscovery
};

private:

const RooArgSet*	fCachedBestFitParams
RooArgSet	fConditionalObs	conditional observables
RooArgSet*	fDetailedOutput	!
bool	fDetailedOutputEnabled
bool	fDetailedOutputWithErrorsAndPulls
Bool_t	fLOffset
RooAbsData*	fLastData
RooStats::ProfileLikelihoodTestStat::LimitType	fLimitType
TString	fMinimizer
RooAbsReal*	fNll	!
RooAbsPdf*	fPdf
Int_t	fPrintLevel
Bool_t	fReuseNll
Bool_t	fSigned
Int_t	fStrategy
Double_t	fTolerance
TString	fVarName
static Bool_t	fgAlwaysReuseNll

Class Charts

Inheritance Inherited Members Includes Libraries

Function documentation

ProfileLikelihoodTestStat()

 Proof constructor. Do not use.

ProfileLikelihoodTestStat(RooAbsPdf& pdf)

virtual ~ProfileLikelihoodTestStat()

void SetOneSided(Bool_t flag = true)

LM use default copy constructor and assignment copying the pointers. Is this what we want ?

{fLimitType = (flag ? oneSided : twoSided);}

void SetOneSidedDiscovery(Bool_t flag = true)

{fLimitType = (flag ? oneSidedDiscovery : twoSided);}

void SetSigned(Bool_t flag = true)

void SetOneSidedDiscovery(Bool_t flag=true) {fOneSidedDiscovery = flag;}

{fSigned = flag;}

bool IsTwoSided() const

{ return fLimitType == twoSided; }

bool IsOneSidedDiscovery() const

{ return fLimitType == oneSidedDiscovery; }

void SetAlwaysReuseNLL(Bool_t flag)

void SetReuseNLL(Bool_t flag)

{ fReuseNll = flag ; }

void SetLOffset(Bool_t flag = kTRUE)

{ fLOffset = flag ; }

void SetMinimizer(const char* minimizer)

{ fMinimizer=minimizer;}

void SetStrategy(Int_t strategy)

{fStrategy=strategy;}

void SetTolerance(double tol)

{fTolerance=tol;}

void SetPrintLevel(Int_t printlevel)

{fPrintLevel=printlevel;}

Double_t Evaluate(RooAbsData& data, RooArgSet& paramsOfInterest)

 Main interface to evaluate the test statistic on a dataset

return EvaluateProfileLikelihood(int type, RooAbsData& data, RooArgSet& paramsOfInterest)

void EnableDetailedOutput(bool e = true, bool withErrorsAndPulls = false)

const RooArgSet* GetDetailedOutput(void)

 Returns detailed output. The value returned by this function is updated after each call to Evaluate().
 The returned RooArgSet contains the following:
 <ul>
 <li> the minimum nll, fitstatus and convergence quality for each fit </li>
 <li> for each fit and for each non-constant parameter, the value, error and pull of the parameter are stored </li>
 </ul>

void SetConditionalObservables(const RooArgSet& set)

 set the conditional observables which will be used when creating the NLL
 so the pdf's will not be normalized on the conditional observables when computing the NLL

{fConditionalObs.removeAll(); fConditionalObs.add(set);}

void SetVarName(const char* name)

{ fVarName = name; }

const TString GetVarName() const

{return fVarName;}

RooAbsPdf * GetPdf() const

{ return fPdf; }

RooFitResult* GetMinNLL()

      const bool PValueIsRightTail(void) { return false; } // overwrites default