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RooStats::HypoTestResult Class Reference

HypoTestResult is a base class for results from hypothesis tests.

Any tool inheriting from HypoTestCalculator can return a HypoTestResult. As such, it stores a p-value for the null-hypothesis (eg. background-only) and an alternate hypothesis (eg. signal+background). The p-values can also be transformed into confidence levels ( \(CL_{b}\), \(CL_{s+b}\)) in a trivial way. The ratio of the \(CL_{s+b}\) to \(CL_{b}\) is often called \(CL_{s}\), and is considered useful, though it is not a probability. Finally, the p-value of the null can be transformed into a number of equivalent Gaussian sigma using the Significance method.

The p-value of the null for a given test statistic is rigorously defined and this is the starting point for the following conventions.

Conventions used in this class

The p-value for the null and alternate are on the same side of the observed value of the test statistic. This is the more standard convention and avoids confusion when doing inverted tests.

For exclusion, we also want the formula \(CL_{s} = CL_{s+b} / CL_{b}\) to hold which therefore defines our conventions for \(CL_{s+b}\) and \(CL_{b}\). \(CL_{s}\) was specifically invented for exclusion and therefore all quantities need be related through the assignments as they are for exclusion: \(CL_{s+b} = p_{s+b}\); \(CL_{b} = p_{b}\). This is derived by considering the scenarios of a powerful and not powerful inverted test, where for the not so powerful test, \(CL_{s}\) must be close to one.

For results of Hypothesis tests, \(CL_{s}\) has no similar direct interpretation as for exclusion and can be larger than one.

Definition at line 22 of file HypoTestResult.h.

Public Member Functions

 HypoTestResult (const char *name, Double_t nullp, Double_t altp)
 constructor from name, null and alternate p values
 
 HypoTestResult (const char *name=0)
 default constructor
 
 HypoTestResult (const HypoTestResult &other)
 copy constructor
 
virtual ~HypoTestResult ()
 destructor
 
virtual Double_t AlternatePValue () const
 Return p-value for alternate hypothesis.
 
virtual void Append (const HypoTestResult *other)
 add values from another HypoTestResult
 
virtual Double_t CLb () const
 Convert NullPValue into a "confidence level".
 
Double_t CLbError () const
 The error on the "confidence level" of the null hypothesis.
 
virtual Double_t CLs () const
 \(CL_{s}\) is simply \(CL_{s+b}/CL_{b}\) (not a method, but a quantity)
 
Double_t CLsError () const
 The error on the ratio \(CL_{s+b}/CL_{b}\).
 
virtual Double_t CLsplusb () const
 Convert AlternatePValue into a "confidence level".
 
Double_t CLsplusbError () const
 The error on the "confidence level" of the alternative hypothesis.
 
const RooArgListGetAllTestStatisticsData (void) const
 
RooDataSetGetAltDetailedOutput (void) const
 
SamplingDistributionGetAltDistribution (void) const
 
Bool_t GetBackGroundIsAlt (void) const
 
RooDataSetGetFitInfo () const
 
RooDataSetGetNullDetailedOutput (void) const
 
SamplingDistributionGetNullDistribution (void) const
 
Bool_t GetPValueIsRightTail (void) const
 
Double_t GetTestStatisticData (void) const
 
Bool_t HasTestStatisticData (void) const
 
virtual Double_t NullPValue () const
 Return p-value for null hypothesis.
 
Double_t NullPValueError () const
 The error on the Null p-value.
 
HypoTestResultoperator= (const HypoTestResult &other)
 assignment operator
 
void Print (const Option_t *="") const
 Print out some information about the results Note: use Alt/Null labels for the hypotheses here as the Null might be the s+b hypothesis.
 
void SetAllTestStatisticsData (const RooArgList *tsd)
 
void SetAltDetailedOutput (RooDataSet *d)
 
void SetAltDistribution (SamplingDistribution *alt)
 
void SetBackgroundAsAlt (Bool_t l=kTRUE)
 
void SetFitInfo (RooDataSet *d)
 
void SetNullDetailedOutput (RooDataSet *d)
 
void SetNullDistribution (SamplingDistribution *null)
 
void SetPValueIsRightTail (Bool_t pr)
 
void SetTestStatisticData (const Double_t tsd)
 
virtual Double_t Significance () const
 familiar name for the Null p-value in terms of 1-sided Gaussian significance
 
Double_t SignificanceError () const
 The error on the significance, computed from NullPValueError via error propagation.
 
- Public Member Functions inherited from TNamed
 TNamed ()
 
 TNamed (const char *name, const char *title)
 
 TNamed (const TNamed &named)
 TNamed copy ctor.
 
 TNamed (const TString &name, const TString &title)
 
virtual ~TNamed ()
 TNamed destructor.
 
virtual void Clear (Option_t *option="")
 Set name and title to empty strings ("").
 
virtual TObjectClone (const char *newname="") const
 Make a clone of an object using the Streamer facility.
 
virtual Int_t Compare (const TObject *obj) const
 Compare two TNamed objects.
 
virtual void Copy (TObject &named) const
 Copy this to obj.
 
virtual void FillBuffer (char *&buffer)
 Encode TNamed into output buffer.
 
virtual const char * GetName () const
 Returns name of object.
 
virtual const char * GetTitle () const
 Returns title of object.
 
virtual ULong_t Hash () const
 Return hash value for this object.
 
virtual Bool_t IsSortable () const
 
virtual void ls (Option_t *option="") const
 List TNamed name and title.
 
TNamedoperator= (const TNamed &rhs)
 TNamed assignment operator.
 
virtual void Print (Option_t *option="") const
 Print TNamed name and title.
 
virtual void SetName (const char *name)
 Set the name of the TNamed.
 
virtual void SetNameTitle (const char *name, const char *title)
 Set all the TNamed parameters (name and title).
 
virtual void SetTitle (const char *title="")
 Set the title of the TNamed.
 
virtual Int_t Sizeof () const
 Return size of the TNamed part of the TObject.
 
- Public Member Functions inherited from TObject
 TObject ()
 TObject constructor.
 
 TObject (const TObject &object)
 TObject copy ctor.
 
virtual ~TObject ()
 TObject destructor.
 
void AbstractMethod (const char *method) const
 Use this method to implement an "abstract" method that you don't want to leave purely abstract.
 
virtual void AppendPad (Option_t *option="")
 Append graphics object to current pad.
 
virtual void Browse (TBrowser *b)
 Browse object. May be overridden for another default action.
 
ULong_t CheckedHash ()
 Check and record whether this class has a consistent Hash/RecursiveRemove setup (*) and then return the regular Hash value for this object.
 
virtual const char * ClassName () const
 Returns name of class to which the object belongs.
 
virtual void Delete (Option_t *option="")
 Delete this object.
 
virtual Int_t DistancetoPrimitive (Int_t px, Int_t py)
 Computes distance from point (px,py) to the object.
 
virtual void Draw (Option_t *option="")
 Default Draw method for all objects.
 
virtual void DrawClass () const
 Draw class inheritance tree of the class to which this object belongs.
 
virtual TObjectDrawClone (Option_t *option="") const
 Draw a clone of this object in the current selected pad for instance with: gROOT->SetSelectedPad(gPad).
 
virtual void Dump () const
 Dump contents of object on stdout.
 
virtual void Error (const char *method, const char *msgfmt,...) const
 Issue error message.
 
virtual void Execute (const char *method, const char *params, Int_t *error=0)
 Execute method on this object with the given parameter string, e.g.
 
virtual void Execute (TMethod *method, TObjArray *params, Int_t *error=0)
 Execute method on this object with parameters stored in the TObjArray.
 
virtual void ExecuteEvent (Int_t event, Int_t px, Int_t py)
 Execute action corresponding to an event at (px,py).
 
virtual void Fatal (const char *method, const char *msgfmt,...) const
 Issue fatal error message.
 
virtual TObjectFindObject (const char *name) const
 Must be redefined in derived classes.
 
virtual TObjectFindObject (const TObject *obj) const
 Must be redefined in derived classes.
 
virtual Option_tGetDrawOption () const
 Get option used by the graphics system to draw this object.
 
virtual const char * GetIconName () const
 Returns mime type name of object.
 
virtual char * GetObjectInfo (Int_t px, Int_t py) const
 Returns string containing info about the object at position (px,py).
 
virtual Option_tGetOption () const
 
virtual UInt_t GetUniqueID () const
 Return the unique object id.
 
virtual Bool_t HandleTimer (TTimer *timer)
 Execute action in response of a timer timing out.
 
Bool_t HasInconsistentHash () const
 Return true is the type of this object is known to have an inconsistent setup for Hash and RecursiveRemove (i.e.
 
virtual void Info (const char *method, const char *msgfmt,...) const
 Issue info message.
 
virtual Bool_t InheritsFrom (const char *classname) const
 Returns kTRUE if object inherits from class "classname".
 
virtual Bool_t InheritsFrom (const TClass *cl) const
 Returns kTRUE if object inherits from TClass cl.
 
virtual void Inspect () const
 Dump contents of this object in a graphics canvas.
 
void InvertBit (UInt_t f)
 
Bool_t IsDestructed () const
 IsDestructed.
 
virtual Bool_t IsEqual (const TObject *obj) const
 Default equal comparison (objects are equal if they have the same address in memory).
 
virtual Bool_t IsFolder () const
 Returns kTRUE in case object contains browsable objects (like containers or lists of other objects).
 
R__ALWAYS_INLINE Bool_t IsOnHeap () const
 
R__ALWAYS_INLINE Bool_t IsZombie () const
 
void MayNotUse (const char *method) const
 Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary).
 
virtual Bool_t Notify ()
 This method must be overridden to handle object notification.
 
void Obsolete (const char *method, const char *asOfVers, const char *removedFromVers) const
 Use this method to declare a method obsolete.
 
void operator delete (void *ptr)
 Operator delete.
 
void operator delete[] (void *ptr)
 Operator delete [].
 
voidoperator new (size_t sz)
 
voidoperator new (size_t sz, void *vp)
 
voidoperator new[] (size_t sz)
 
voidoperator new[] (size_t sz, void *vp)
 
TObjectoperator= (const TObject &rhs)
 TObject assignment operator.
 
virtual void Paint (Option_t *option="")
 This method must be overridden if a class wants to paint itself.
 
virtual void Pop ()
 Pop on object drawn in a pad to the top of the display list.
 
virtual Int_t Read (const char *name)
 Read contents of object with specified name from the current directory.
 
virtual void RecursiveRemove (TObject *obj)
 Recursively remove this object from a list.
 
void ResetBit (UInt_t f)
 
virtual void SaveAs (const char *filename="", Option_t *option="") const
 Save this object in the file specified by filename.
 
virtual void SavePrimitive (std::ostream &out, Option_t *option="")
 Save a primitive as a C++ statement(s) on output stream "out".
 
void SetBit (UInt_t f)
 
void SetBit (UInt_t f, Bool_t set)
 Set or unset the user status bits as specified in f.
 
virtual void SetDrawOption (Option_t *option="")
 Set drawing option for object.
 
virtual void SetUniqueID (UInt_t uid)
 Set the unique object id.
 
virtual void SysError (const char *method, const char *msgfmt,...) const
 Issue system error message.
 
R__ALWAYS_INLINE Bool_t TestBit (UInt_t f) const
 
Int_t TestBits (UInt_t f) const
 
virtual void UseCurrentStyle ()
 Set current style settings in this object This function is called when either TCanvas::UseCurrentStyle or TROOT::ForceStyle have been invoked.
 
virtual void Warning (const char *method, const char *msgfmt,...) const
 Issue warning message.
 
virtual Int_t Write (const char *name=0, Int_t option=0, Int_t bufsize=0)
 Write this object to the current directory.
 
virtual Int_t Write (const char *name=0, Int_t option=0, Int_t bufsize=0) const
 Write this object to the current directory.
 

Protected Attributes

const RooArgListfAllTestStatisticsData
 
RooDataSetfAltDetailedOutput
 
SamplingDistributionfAltDistr
 
Double_t fAlternatePValue
 
Double_t fAlternatePValueError
 
Bool_t fBackgroundIsAlt
 
std::unique_ptr< RooDataSetfFitInfo
 
RooDataSetfNullDetailedOutput
 
SamplingDistributionfNullDistr
 
Double_t fNullPValue
 
Double_t fNullPValueError
 
Bool_t fPValueIsRightTail
 
Double_t fTestStatisticData
 
- Protected Attributes inherited from TNamed
TString fName
 
TString fTitle
 

Private Member Functions

void UpdatePValue (const SamplingDistribution *distr, Double_t &pvalue, Double_t &perror, Bool_t pIsRightTail)
 updates the pvalue if sufficient data is available
 

Additional Inherited Members

- Public Types inherited from TObject
enum  {
  kIsOnHeap = 0x01000000 , kNotDeleted = 0x02000000 , kZombie = 0x04000000 , kInconsistent = 0x08000000 ,
  kBitMask = 0x00ffffff
}
 
enum  { kSingleKey = BIT(0) , kOverwrite = BIT(1) , kWriteDelete = BIT(2) }
 
enum  EDeprecatedStatusBits { kObjInCanvas = BIT(3) }
 
enum  EStatusBits {
  kCanDelete = BIT(0) , kMustCleanup = BIT(3) , kIsReferenced = BIT(4) , kHasUUID = BIT(5) ,
  kCannotPick = BIT(6) , kNoContextMenu = BIT(8) , kInvalidObject = BIT(13)
}
 
- Static Public Member Functions inherited from TObject
static Longptr_t GetDtorOnly ()
 Return destructor only flag.
 
static Bool_t GetObjectStat ()
 Get status of object stat flag.
 
static void SetDtorOnly (void *obj)
 Set destructor only flag.
 
static void SetObjectStat (Bool_t stat)
 Turn on/off tracking of objects in the TObjectTable.
 
- Protected Types inherited from TObject
enum  { kOnlyPrepStep = BIT(3) }
 
- Protected Member Functions inherited from TObject
virtual void DoError (int level, const char *location, const char *fmt, va_list va) const
 Interface to ErrorHandler (protected).
 
void MakeZombie ()
 

#include <RooStats/HypoTestResult.h>

Inheritance diagram for RooStats::HypoTestResult:
[legend]

Constructor & Destructor Documentation

◆ HypoTestResult() [1/3]

HypoTestResult::HypoTestResult ( const char *  name = 0)
explicit

default constructor

Default constructor.

Definition at line 77 of file HypoTestResult.cxx.

◆ HypoTestResult() [2/3]

HypoTestResult::HypoTestResult ( const HypoTestResult other)

copy constructor

Definition at line 109 of file HypoTestResult.cxx.

◆ HypoTestResult() [3/3]

HypoTestResult::HypoTestResult ( const char *  name,
Double_t  nullp,
Double_t  altp 
)

constructor from name, null and alternate p values

Alternate constructor.

Definition at line 93 of file HypoTestResult.cxx.

◆ ~HypoTestResult()

HypoTestResult::~HypoTestResult ( )
virtual

destructor

Destructor.

Definition at line 126 of file HypoTestResult.cxx.

Member Function Documentation

◆ AlternatePValue()

virtual Double_t RooStats::HypoTestResult::AlternatePValue ( ) const
inlinevirtual

Return p-value for alternate hypothesis.

Reimplemented in RooStats::HybridResult.

Definition at line 48 of file HypoTestResult.h.

◆ Append()

void HypoTestResult::Append ( const HypoTestResult other)
virtual

add values from another HypoTestResult

Add additional toy-MC experiments to the current results.

Use the data test statistics of the added object if it is not already set (otherwise, ignore the new one).

Definition at line 171 of file HypoTestResult.cxx.

◆ CLb()

virtual Double_t RooStats::HypoTestResult::CLb ( ) const
inlinevirtual

Convert NullPValue into a "confidence level".

Definition at line 51 of file HypoTestResult.h.

◆ CLbError()

Double_t HypoTestResult::CLbError ( ) const

The error on the "confidence level" of the null hypothesis.

compute \(CL_{b}\) error \(CL_{b}\) = 1 - NullPValue() must use opposite condition that routine above

Definition at line 273 of file HypoTestResult.cxx.

◆ CLs()

virtual Double_t RooStats::HypoTestResult::CLs ( ) const
inlinevirtual

\(CL_{s}\) is simply \(CL_{s+b}/CL_{b}\) (not a method, but a quantity)

Definition at line 57 of file HypoTestResult.h.

◆ CLsError()

Double_t HypoTestResult::CLsError ( ) const

The error on the ratio \(CL_{s+b}/CL_{b}\).

Returns an estimate of the error on \(CL_{s}\) through combination of the errors on \(CL_{b}\) and \(CL_{s+b}\):

\[ \sigma_{CL_s} = CL_s \sqrt{\left( \frac{\sigma_{CL_{s+b}}}{CL_{s+b}} \right)^2 + \left( \frac{\sigma_{CL_{b}}}{CL_{b}} \right)^2} \]

Definition at line 298 of file HypoTestResult.cxx.

◆ CLsplusb()

virtual Double_t RooStats::HypoTestResult::CLsplusb ( ) const
inlinevirtual

Convert AlternatePValue into a "confidence level".

Definition at line 54 of file HypoTestResult.h.

◆ CLsplusbError()

Double_t HypoTestResult::CLsplusbError ( ) const

The error on the "confidence level" of the alternative hypothesis.

Definition at line 279 of file HypoTestResult.cxx.

◆ GetAllTestStatisticsData()

const RooArgList * RooStats::HypoTestResult::GetAllTestStatisticsData ( void  ) const
inline

Definition at line 76 of file HypoTestResult.h.

◆ GetAltDetailedOutput()

RooDataSet * RooStats::HypoTestResult::GetAltDetailedOutput ( void  ) const
inline

Definition at line 73 of file HypoTestResult.h.

◆ GetAltDistribution()

SamplingDistribution * RooStats::HypoTestResult::GetAltDistribution ( void  ) const
inline

Definition at line 71 of file HypoTestResult.h.

◆ GetBackGroundIsAlt()

Bool_t RooStats::HypoTestResult::GetBackGroundIsAlt ( void  ) const
inline

Definition at line 91 of file HypoTestResult.h.

◆ GetFitInfo()

RooDataSet * RooStats::HypoTestResult::GetFitInfo ( ) const
inline

Definition at line 74 of file HypoTestResult.h.

◆ GetNullDetailedOutput()

RooDataSet * RooStats::HypoTestResult::GetNullDetailedOutput ( void  ) const
inline

Definition at line 72 of file HypoTestResult.h.

◆ GetNullDistribution()

SamplingDistribution * RooStats::HypoTestResult::GetNullDistribution ( void  ) const
inline

Definition at line 70 of file HypoTestResult.h.

◆ GetPValueIsRightTail()

Bool_t RooStats::HypoTestResult::GetPValueIsRightTail ( void  ) const
inline

Definition at line 88 of file HypoTestResult.h.

◆ GetTestStatisticData()

Double_t RooStats::HypoTestResult::GetTestStatisticData ( void  ) const
inline

Definition at line 75 of file HypoTestResult.h.

◆ HasTestStatisticData()

Bool_t HypoTestResult::HasTestStatisticData ( void  ) const

Definition at line 257 of file HypoTestResult.cxx.

◆ NullPValue()

virtual Double_t RooStats::HypoTestResult::NullPValue ( ) const
inlinevirtual

Return p-value for null hypothesis.

Reimplemented in RooStats::HybridResult.

Definition at line 45 of file HypoTestResult.h.

◆ NullPValueError()

Double_t HypoTestResult::NullPValueError ( ) const

The error on the Null p-value.

Definition at line 263 of file HypoTestResult.cxx.

◆ operator=()

HypoTestResult & HypoTestResult::operator= ( const HypoTestResult other)

assignment operator

Definition at line 140 of file HypoTestResult.cxx.

◆ Print()

void HypoTestResult::Print ( const Option_t = "") const

Print out some information about the results Note: use Alt/Null labels for the hypotheses here as the Null might be the s+b hypothesis.

Definition at line 339 of file HypoTestResult.cxx.

◆ SetAllTestStatisticsData()

void HypoTestResult::SetAllTestStatisticsData ( const RooArgList tsd)

Definition at line 233 of file HypoTestResult.cxx.

◆ SetAltDetailedOutput()

void RooStats::HypoTestResult::SetAltDetailedOutput ( RooDataSet d)
inline

Definition at line 81 of file HypoTestResult.h.

◆ SetAltDistribution()

void HypoTestResult::SetAltDistribution ( SamplingDistribution alt)

Definition at line 210 of file HypoTestResult.cxx.

◆ SetBackgroundAsAlt()

void RooStats::HypoTestResult::SetBackgroundAsAlt ( Bool_t  l = kTRUE)
inline

Definition at line 90 of file HypoTestResult.h.

◆ SetFitInfo()

void RooStats::HypoTestResult::SetFitInfo ( RooDataSet d)
inline

Definition at line 83 of file HypoTestResult.h.

◆ SetNullDetailedOutput()

void RooStats::HypoTestResult::SetNullDetailedOutput ( RooDataSet d)
inline

Definition at line 82 of file HypoTestResult.h.

◆ SetNullDistribution()

void HypoTestResult::SetNullDistribution ( SamplingDistribution null)

Definition at line 217 of file HypoTestResult.cxx.

◆ SetPValueIsRightTail()

void HypoTestResult::SetPValueIsRightTail ( Bool_t  pr)

Definition at line 248 of file HypoTestResult.cxx.

◆ SetTestStatisticData()

void HypoTestResult::SetTestStatisticData ( const Double_t  tsd)

Definition at line 224 of file HypoTestResult.cxx.

◆ Significance()

virtual Double_t RooStats::HypoTestResult::Significance ( ) const
inlinevirtual

familiar name for the Null p-value in terms of 1-sided Gaussian significance

Definition at line 68 of file HypoTestResult.h.

◆ SignificanceError()

Double_t HypoTestResult::SignificanceError ( ) const

The error on the significance, computed from NullPValueError via error propagation.

Taylor expansion series approximation for standard deviation (error propagation)

Definition at line 286 of file HypoTestResult.cxx.

◆ UpdatePValue()

void HypoTestResult::UpdatePValue ( const SamplingDistribution distr,
Double_t pvalue,
Double_t perror,
Bool_t  pIsRightTail 
)
private

updates the pvalue if sufficient data is available

Definition at line 316 of file HypoTestResult.cxx.

Member Data Documentation

◆ fAllTestStatisticsData

const RooArgList* RooStats::HypoTestResult::fAllTestStatisticsData
protected

Definition at line 122 of file HypoTestResult.h.

◆ fAltDetailedOutput

RooDataSet* RooStats::HypoTestResult::fAltDetailedOutput
protected

Definition at line 126 of file HypoTestResult.h.

◆ fAltDistr

SamplingDistribution* RooStats::HypoTestResult::fAltDistr
protected

Definition at line 124 of file HypoTestResult.h.

◆ fAlternatePValue

Double_t RooStats::HypoTestResult::fAlternatePValue
mutableprotected

Definition at line 118 of file HypoTestResult.h.

◆ fAlternatePValueError

Double_t RooStats::HypoTestResult::fAlternatePValueError
mutableprotected

Definition at line 120 of file HypoTestResult.h.

◆ fBackgroundIsAlt

Bool_t RooStats::HypoTestResult::fBackgroundIsAlt
protected

Definition at line 129 of file HypoTestResult.h.

◆ fFitInfo

std::unique_ptr<RooDataSet> RooStats::HypoTestResult::fFitInfo
protected

Definition at line 127 of file HypoTestResult.h.

◆ fNullDetailedOutput

RooDataSet* RooStats::HypoTestResult::fNullDetailedOutput
protected

Definition at line 125 of file HypoTestResult.h.

◆ fNullDistr

SamplingDistribution* RooStats::HypoTestResult::fNullDistr
protected

Definition at line 123 of file HypoTestResult.h.

◆ fNullPValue

Double_t RooStats::HypoTestResult::fNullPValue
mutableprotected

Definition at line 117 of file HypoTestResult.h.

◆ fNullPValueError

Double_t RooStats::HypoTestResult::fNullPValueError
mutableprotected

Definition at line 119 of file HypoTestResult.h.

◆ fPValueIsRightTail

Bool_t RooStats::HypoTestResult::fPValueIsRightTail
protected

Definition at line 128 of file HypoTestResult.h.

◆ fTestStatisticData

Double_t RooStats::HypoTestResult::fTestStatisticData
protected

Definition at line 121 of file HypoTestResult.h.

Libraries for RooStats::HypoTestResult:

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