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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 nullp, double altp)
 constructor from name, null and alternate p values
 
 HypoTestResult (const char *name=nullptr)
 default constructor
 
 HypoTestResult (const HypoTestResult &other)
 copy constructor
 
 ~HypoTestResult () override
 destructor
 
virtual double AlternatePValue () const
 Return p-value for alternate hypothesis.
 
virtual void Append (const HypoTestResult *other)
 add values from another HypoTestResult
 
virtual double CLb () const
 Convert NullPValue into a "confidence level".
 
double CLbError () const
 The error on the "confidence level" of the null hypothesis.
 
virtual double CLs () const
 \(CL_{s}\) is simply \(CL_{s+b}/CL_{b}\) (not a method, but a quantity)
 
double CLsError () const
 The error on the ratio \(CL_{s+b}/CL_{b}\).
 
virtual double CLsplusb () const
 Convert AlternatePValue into a "confidence level".
 
double CLsplusbError () const
 The error on the "confidence level" of the alternative hypothesis.
 
const RooArgListGetAllTestStatisticsData (void) const
 
RooDataSetGetAltDetailedOutput (void) const
 
SamplingDistributionGetAltDistribution (void) const
 
bool GetBackGroundIsAlt (void) const
 
RooDataSetGetFitInfo () const
 
RooDataSetGetNullDetailedOutput (void) const
 
SamplingDistributionGetNullDistribution (void) const
 
bool GetPValueIsRightTail (void) const
 
double GetTestStatisticData (void) const
 
bool HasTestStatisticData (void) const
 
TClassIsA () const override
 
virtual double NullPValue () const
 Return p-value for null hypothesis.
 
double NullPValueError () const
 The error on the Null p-value.
 
HypoTestResultoperator= (const HypoTestResult &other)
 assignment operator
 
void Print (const Option_t *="") const override
 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 SetAltPValue (double pvalue)
 
void SetAltPValueError (double err)
 
void SetBackgroundAsAlt (bool l=true)
 
void SetFitInfo (RooDataSet *d)
 
void SetNullDetailedOutput (RooDataSet *d)
 
void SetNullDistribution (SamplingDistribution *null)
 
void SetNullPValue (double pvalue)
 
void SetNullPValueError (double err)
 
void SetPValueIsRightTail (bool pr)
 
void SetTestStatisticData (const double tsd)
 
virtual double Significance () const
 familiar name for the Null p-value in terms of 1-sided Gaussian significance
 
double SignificanceError () const
 The error on the significance, computed from NullPValueError via error propagation.
 
void Streamer (TBuffer &) override
 Stream an object of class TObject.
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 
- 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.
 
void Clear (Option_t *option="") override
 Set name and title to empty strings ("").
 
TObjectClone (const char *newname="") const override
 Make a clone of an object using the Streamer facility.
 
Int_t Compare (const TObject *obj) const override
 Compare two TNamed objects.
 
void Copy (TObject &named) const override
 Copy this to obj.
 
virtual void FillBuffer (char *&buffer)
 Encode TNamed into output buffer.
 
const char * GetName () const override
 Returns name of object.
 
const char * GetTitle () const override
 Returns title of object.
 
ULong_t Hash () const override
 Return hash value for this object.
 
TClassIsA () const override
 
Bool_t IsSortable () const override
 
void ls (Option_t *option="") const override
 List TNamed name and title.
 
TNamedoperator= (const TNamed &rhs)
 TNamed assignment operator.
 
void Print (Option_t *option="") const override
 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.
 
void Streamer (TBuffer &) override
 Stream an object of class TObject.
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 
- 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 with: gROOT->SetSelectedPad(c1).
 
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=nullptr)
 Execute method on this object with the given parameter string, e.g.
 
virtual void Execute (TMethod *method, TObjArray *params, Int_t *error=nullptr)
 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 [].
 
void * operator new (size_t sz)
 
void * operator new (size_t sz, void *vp)
 
void * operator new[] (size_t sz)
 
void * operator 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.
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 
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=nullptr, Int_t option=0, Int_t bufsize=0)
 Write this object to the current directory.
 
virtual Int_t Write (const char *name=nullptr, Int_t option=0, Int_t bufsize=0) const
 Write this object to the current directory.
 

Static Public Member Functions

static TClassClass ()
 
static const char * Class_Name ()
 
static constexpr Version_t Class_Version ()
 
static const char * DeclFileName ()
 
- Static Public Member Functions inherited from TNamed
static TClassClass ()
 
static const char * Class_Name ()
 
static constexpr Version_t Class_Version ()
 
static const char * DeclFileName ()
 
- Static Public Member Functions inherited from TObject
static TClassClass ()
 
static const char * Class_Name ()
 
static constexpr Version_t Class_Version ()
 
static const char * DeclFileName ()
 
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 Attributes

const RooArgListfAllTestStatisticsData
 for the case of multiple test statistics, holds all the results
 
RooDataSetfAltDetailedOutput
 
SamplingDistributionfAltDistr
 
double fAlternatePValue
 p-value for the alternate hypothesis (small number means disfavoured)
 
double fAlternatePValueError
 error of p-value for the alternate hypothesis (small number means disfavoured)
 
bool fBackgroundIsAlt
 
std::unique_ptr< RooDataSetfFitInfo
 
RooDataSetfNullDetailedOutput
 
SamplingDistributionfNullDistr
 
double fNullPValue
 p-value for the null hypothesis (small number means disfavoured)
 
double fNullPValueError
 error of p-value for the null hypothesis (small number means disfavoured)
 
bool fPValueIsRightTail
 
double fTestStatisticData
 result of the test statistic evaluated on data
 
- Protected Attributes inherited from TNamed
TString fName
 
TString fTitle
 

Private Member Functions

void UpdatePValue (const SamplingDistribution *distr, double &pvalue, double &perror, bool 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 = (1ULL << ( 0 )) , kOverwrite = (1ULL << ( 1 )) , kWriteDelete = (1ULL << ( 2 )) }
 
enum  EDeprecatedStatusBits { kObjInCanvas = (1ULL << ( 3 )) }
 
enum  EStatusBits {
  kCanDelete = (1ULL << ( 0 )) , kMustCleanup = (1ULL << ( 3 )) , kIsReferenced = (1ULL << ( 4 )) , kHasUUID = (1ULL << ( 5 )) ,
  kCannotPick = (1ULL << ( 6 )) , kNoContextMenu = (1ULL << ( 8 )) , kInvalidObject = (1ULL << ( 13 ))
}
 
- Protected Types inherited from TObject
enum  { kOnlyPrepStep = (1ULL << ( 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 = nullptr)
explicit

default constructor

Default constructor.

Definition at line 79 of file HypoTestResult.cxx.

◆ HypoTestResult() [2/3]

HypoTestResult::HypoTestResult ( const HypoTestResult other)

copy constructor

Definition at line 111 of file HypoTestResult.cxx.

◆ HypoTestResult() [3/3]

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

constructor from name, null and alternate p values

Alternate constructor.

Definition at line 95 of file HypoTestResult.cxx.

◆ ~HypoTestResult()

HypoTestResult::~HypoTestResult ( )
override

destructor

Destructor.

Definition at line 128 of file HypoTestResult.cxx.

Member Function Documentation

◆ AlternatePValue()

virtual double 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 173 of file HypoTestResult.cxx.

◆ Class()

static TClass * RooStats::HypoTestResult::Class ( )
static
Returns
TClass describing this class

◆ Class_Name()

static const char * RooStats::HypoTestResult::Class_Name ( )
static
Returns
Name of this class

◆ Class_Version()

static constexpr Version_t RooStats::HypoTestResult::Class_Version ( )
inlinestaticconstexpr
Returns
Version of this class

Definition at line 135 of file HypoTestResult.h.

◆ CLb()

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

Convert NullPValue into a "confidence level".

Definition at line 51 of file HypoTestResult.h.

◆ CLbError()

double 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 275 of file HypoTestResult.cxx.

◆ CLs()

virtual double 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 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 300 of file HypoTestResult.cxx.

◆ CLsplusb()

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

Convert AlternatePValue into a "confidence level".

Definition at line 54 of file HypoTestResult.h.

◆ CLsplusbError()

double HypoTestResult::CLsplusbError ( ) const

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

Definition at line 281 of file HypoTestResult.cxx.

◆ DeclFileName()

static const char * RooStats::HypoTestResult::DeclFileName ( )
inlinestatic
Returns
Name of the file containing the class declaration

Definition at line 135 of file HypoTestResult.h.

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

Definition at line 95 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 RooStats::HypoTestResult::GetPValueIsRightTail ( void  ) const
inline

Definition at line 92 of file HypoTestResult.h.

◆ GetTestStatisticData()

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

Definition at line 75 of file HypoTestResult.h.

◆ HasTestStatisticData()

bool HypoTestResult::HasTestStatisticData ( void  ) const

Definition at line 259 of file HypoTestResult.cxx.

◆ IsA()

TClass * RooStats::HypoTestResult::IsA ( ) const
inlineoverridevirtual
Returns
TClass describing current object

Reimplemented from TObject.

Definition at line 135 of file HypoTestResult.h.

◆ NullPValue()

virtual double 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 HypoTestResult::NullPValueError ( ) const

The error on the Null p-value.

Definition at line 265 of file HypoTestResult.cxx.

◆ operator=()

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

assignment operator

Definition at line 142 of file HypoTestResult.cxx.

◆ Print()

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

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 341 of file HypoTestResult.cxx.

◆ SetAllTestStatisticsData()

void HypoTestResult::SetAllTestStatisticsData ( const RooArgList tsd)

Definition at line 235 of file HypoTestResult.cxx.

◆ SetAltDetailedOutput()

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

Definition at line 85 of file HypoTestResult.h.

◆ SetAltDistribution()

void HypoTestResult::SetAltDistribution ( SamplingDistribution alt)

Definition at line 212 of file HypoTestResult.cxx.

◆ SetAltPValue()

void RooStats::HypoTestResult::SetAltPValue ( double  pvalue)
inline

Definition at line 81 of file HypoTestResult.h.

◆ SetAltPValueError()

void RooStats::HypoTestResult::SetAltPValueError ( double  err)
inline

Definition at line 82 of file HypoTestResult.h.

◆ SetBackgroundAsAlt()

void RooStats::HypoTestResult::SetBackgroundAsAlt ( bool  l = true)
inline

Definition at line 94 of file HypoTestResult.h.

◆ SetFitInfo()

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

Definition at line 87 of file HypoTestResult.h.

◆ SetNullDetailedOutput()

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

Definition at line 86 of file HypoTestResult.h.

◆ SetNullDistribution()

void HypoTestResult::SetNullDistribution ( SamplingDistribution null)

Definition at line 219 of file HypoTestResult.cxx.

◆ SetNullPValue()

void RooStats::HypoTestResult::SetNullPValue ( double  pvalue)
inline

Definition at line 79 of file HypoTestResult.h.

◆ SetNullPValueError()

void RooStats::HypoTestResult::SetNullPValueError ( double  err)
inline

Definition at line 80 of file HypoTestResult.h.

◆ SetPValueIsRightTail()

void HypoTestResult::SetPValueIsRightTail ( bool  pr)

Definition at line 250 of file HypoTestResult.cxx.

◆ SetTestStatisticData()

void HypoTestResult::SetTestStatisticData ( const double  tsd)

Definition at line 226 of file HypoTestResult.cxx.

◆ Significance()

virtual double 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 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 288 of file HypoTestResult.cxx.

◆ Streamer()

void RooStats::HypoTestResult::Streamer ( TBuffer R__b)
overridevirtual

Stream an object of class TObject.

Reimplemented from TObject.

◆ StreamerNVirtual()

void RooStats::HypoTestResult::StreamerNVirtual ( TBuffer ClassDef_StreamerNVirtual_b)
inline

Definition at line 135 of file HypoTestResult.h.

◆ UpdatePValue()

void HypoTestResult::UpdatePValue ( const SamplingDistribution distr,
double pvalue,
double perror,
bool  pIsRightTail 
)
private

updates the pvalue if sufficient data is available

Definition at line 318 of file HypoTestResult.cxx.

Member Data Documentation

◆ fAllTestStatisticsData

const RooArgList* RooStats::HypoTestResult::fAllTestStatisticsData
protected

for the case of multiple test statistics, holds all the results

Definition at line 126 of file HypoTestResult.h.

◆ fAltDetailedOutput

RooDataSet* RooStats::HypoTestResult::fAltDetailedOutput
protected

Definition at line 130 of file HypoTestResult.h.

◆ fAltDistr

SamplingDistribution* RooStats::HypoTestResult::fAltDistr
protected

Definition at line 128 of file HypoTestResult.h.

◆ fAlternatePValue

double RooStats::HypoTestResult::fAlternatePValue
mutableprotected

p-value for the alternate hypothesis (small number means disfavoured)

Definition at line 122 of file HypoTestResult.h.

◆ fAlternatePValueError

double RooStats::HypoTestResult::fAlternatePValueError
mutableprotected

error of p-value for the alternate hypothesis (small number means disfavoured)

Definition at line 124 of file HypoTestResult.h.

◆ fBackgroundIsAlt

bool RooStats::HypoTestResult::fBackgroundIsAlt
protected

Definition at line 133 of file HypoTestResult.h.

◆ fFitInfo

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

Definition at line 131 of file HypoTestResult.h.

◆ fNullDetailedOutput

RooDataSet* RooStats::HypoTestResult::fNullDetailedOutput
protected

Definition at line 129 of file HypoTestResult.h.

◆ fNullDistr

SamplingDistribution* RooStats::HypoTestResult::fNullDistr
protected

Definition at line 127 of file HypoTestResult.h.

◆ fNullPValue

double RooStats::HypoTestResult::fNullPValue
mutableprotected

p-value for the null hypothesis (small number means disfavoured)

Definition at line 121 of file HypoTestResult.h.

◆ fNullPValueError

double RooStats::HypoTestResult::fNullPValueError
mutableprotected

error of p-value for the null hypothesis (small number means disfavoured)

Definition at line 123 of file HypoTestResult.h.

◆ fPValueIsRightTail

bool RooStats::HypoTestResult::fPValueIsRightTail
protected

Definition at line 132 of file HypoTestResult.h.

◆ fTestStatisticData

double RooStats::HypoTestResult::fTestStatisticData
protected

result of the test statistic evaluated on data

Definition at line 125 of file HypoTestResult.h.

Libraries for RooStats::HypoTestResult:

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