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ROOT » ROOFIT » ROOSTATS » RooStats::SamplingDistribution

class RooStats::SamplingDistribution: public TNamed


SamplingDistribution :

This class simply holds a sampling distribution of some test statistic.
The distribution can either be an empirical distribution (eg. the samples themselves) or
a weighted set of points (eg. for the FFT method).
The class supports merging.

Function Members (Methods)

public:

virtual	~SamplingDistribution()
void	TObject::AbstractMethod(const char* method) const
void	Add(const RooStats::SamplingDistribution* other)
virtual void	TObject::AppendPad(Option_t* option = "")
virtual void	TObject::Browse(TBrowser* b)
Double_t	CDF(Double_t x) const
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 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 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
const vector<Double_t>&	GetSampleWeights() const
const vector<Double_t>&	GetSamplingDistribution() const
Int_t	GetSize() const
virtual const char*	TNamed::GetTitle() const
virtual UInt_t	TObject::GetUniqueID() const
const TString	GetVarName() 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
Double_t	Integral(Double_t low, Double_t high, Bool_t normalize = kTRUE, Bool_t lowClosed = kTRUE, Bool_t highClosed = kFALSE) const
Double_t	IntegralAndError(Double_t& error, Double_t low, Double_t high, Bool_t normalize = kTRUE, Bool_t lowClosed = kTRUE, Bool_t highClosed = kFALSE) const
Double_t	InverseCDF(Double_t pvalue)
Double_t	InverseCDF(Double_t pvalue, Double_t sigmaVariaton, Double_t& inverseVariation)
Double_t	InverseCDFInterpolate(Double_t pvalue)
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()
void	TObject::Obsolete(const char* method, const char* asOfVers, const char* removedFromVers) const
void	TObject::operator delete(void* ptr)
void	TObject::operator delete(void* ptr, void* vp)
void	TObject::operator delete[](void* ptr)
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::SamplingDistribution&	operator=(const RooStats::SamplingDistribution&)
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)
RooStats::SamplingDistribution	SamplingDistribution()
RooStats::SamplingDistribution	SamplingDistribution(const RooStats::SamplingDistribution&)
RooStats::SamplingDistribution	SamplingDistribution(const char* name, const char* title, const char* varName = 0)
RooStats::SamplingDistribution	SamplingDistribution(const char* name, const char* title, vector<Double_t>& samplingDist, const char* varName = 0)
RooStats::SamplingDistribution	SamplingDistribution(const char* name, const char* title, vector<Double_t>& samplingDist, vector<Double_t>& sampleWeights, const char* varName = 0)
RooStats::SamplingDistribution	SamplingDistribution(const char* name, const char* title, RooDataSet& dataSet, const char* columnName = 0, const char* varName = 0)
virtual void	TObject::SaveAs(const char* filename = "", Option_t* option = "") constMENU
virtual void	TObject::SavePrimitive(ostream& out, Option_t* option = "")
void	TObject::SetBit(UInt_t f)
void	TObject::SetBit(UInt_t f, Bool_t set)
virtual void	TObject::SetDrawOption(Option_t* option = "")MENU
static void	TObject::SetDtorOnly(void* obj)
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	TNamed::SetTitle(const char* title = "")MENU
virtual void	TObject::SetUniqueID(UInt_t uid)
virtual void	ShowMembers(TMemberInspector& insp) const
virtual Int_t	TNamed::Sizeof() const
virtual void	Streamer(TBuffer&)
void	StreamerNVirtual(TBuffer& ClassDef_StreamerNVirtual_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:

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

Data Members

public:

static TObject::(anonymous)	TObject::kBitMask
static TObject::EStatusBits	TObject::kCanDelete
static TObject::EStatusBits	TObject::kCannotPick
static TObject::EStatusBits	TObject::kHasUUID
static TObject::EStatusBits	TObject::kInvalidObject
static TObject::(anonymous)	TObject::kIsOnHeap
static TObject::EStatusBits	TObject::kIsReferenced
static TObject::EStatusBits	TObject::kMustCleanup
static TObject::EStatusBits	TObject::kNoContextMenu
static TObject::(anonymous)	TObject::kNotDeleted
static TObject::EStatusBits	TObject::kObjInCanvas
static TObject::(anonymous)	TObject::kOverwrite
static TObject::(anonymous)	TObject::kSingleKey
static TObject::(anonymous)	TObject::kWriteDelete
static TObject::(anonymous)	TObject::kZombie

protected:

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

private:

vector<Double_t>	fSampleWeights	vector of weights for the samples
vector<Double_t>	fSamplingDist	vector of points for the sampling distribution
vector<Double_t>	fSumW	! Chached vector with sum of the weight used to compute integral
vector<Double_t>	fSumW2	! Chached vector with sum of the weight used to compute integral error
TString	fVarName

Class Charts

Inheritance Inherited Members Includes Libraries

Function documentation

SamplingDistribution(const char* name, const char* title, vector<Double_t>& samplingDist, const char* varName = 0)

 SamplingDistribution constructor

SamplingDistribution(const char* name, const char* title, vector<Double_t>& samplingDist, vector<Double_t>& sampleWeights, const char* varName = 0)

 SamplingDistribution constructor

SamplingDistribution(const char* name, const char* title, const char* varName = 0)

 SamplingDistribution constructor (with name and title)

SamplingDistribution(const char* name, const char* title, RooDataSet& dataSet, const char* columnName = 0, const char* varName = 0)

 Creates a SamplingDistribution from a RooDataSet for debugging
 purposes; e.g. if you need a Gaussian type SamplingDistribution
 you can generate it from a Gaussian pdf and use the resulting
 RooDataSet with this constructor.

 The result is the projected distribution onto varName
 marginalizing the other variables.

 If varName is not given, the first variable will be used.
 This is useful mostly for RooDataSets with only one observable.
 check there are any meaningful entries in the given dataset

SamplingDistribution()

 SamplingDistribution default constructor

~SamplingDistribution()

 SamplingDistribution destructor

void Add(const RooStats::SamplingDistribution* other)

 Merge SamplingDistributions (does nothing if NULL is given).
 If variable name was not set before, it is copied from the added
 SamplingDistribution.

Double_t Integral(Double_t low, Double_t high, Bool_t normalize = kTRUE, Bool_t lowClosed = kTRUE, Bool_t highClosed = kFALSE) const

 Returns the integral in the open/closed/mixed interval. Default is [low,high) interval.
 Normalization can be turned off.

void SortValues() const

Double_t IntegralAndError(Double_t& error, Double_t low, Double_t high, Bool_t normalize = kTRUE, Bool_t lowClosed = kTRUE, Bool_t highClosed = kFALSE) const

 Returns the integral in the open/closed/mixed interval. Default is [low,high) interval.
 Normalization can be turned off.
 compute also the error on the integral

Double_t CDF(Double_t x) const

 returns the closed integral [-inf,x]

Double_t InverseCDF(Double_t pvalue)

 returns the inverse of the cumulative distribution function

Double_t InverseCDF(Double_t pvalue, Double_t sigmaVariaton, Double_t& inverseVariation)

 returns the inverse of the cumulative distribution function, with variations depending on number of samples

Double_t InverseCDFInterpolate(Double_t pvalue)

 returns the inverse of the cumulative distribution function

SamplingDistribution(const char* name, const char* title, vector<Double_t>& samplingDist, const char* varName = 0)

 Constructor for SamplingDistribution

Int_t GetSize() const

 size of samples

{return fSamplingDist.size();}

const std::vector<Double_t> & GetSamplingDistribution() const

 Get test statistics values

{return fSamplingDist;}

const std::vector<Double_t> & GetSampleWeights() const

 Get the sampling weights

{return fSampleWeights;}

const TString GetVarName() const

{return fVarName;}