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RooStats::HypoTestInverterResult Class Reference

HypoTestInverterResult class holds the array of hypothesis test results and compute a confidence interval.

Based on the RatioFinder code available in the RooStatsCms package developed by Gregory Schott and Danilo Piparo Ported and adapted to RooStats by Gregory Schott Some contributions to this class have been written by Matthias Wolf (error estimation)

Definition at line 26 of file HypoTestInverterResult.h.

Public Types

enum  InterpolOption_t { kLinear , kSpline }
 
- 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)
}
 

Public Member Functions

 HypoTestInverterResult (const char *name, const RooRealVar &scannedVariable, double cl)
 constructor
 
 HypoTestInverterResult (const char *name=0)
 default constructor
 
 HypoTestInverterResult (const HypoTestInverterResult &other, const char *name)
 copy constructor
 
virtual ~HypoTestInverterResult ()
 destructor
 
bool Add (const HypoTestInverterResult &otherResult)
 merge with the content of another HypoTestInverterResult object
 
bool Add (Double_t x, const HypoTestResult &result)
 add the result of a single point (an HypoTestRsult)
 
int ArraySize () const
 number of entries in the results array
 
double CLb (int index) const
 return the observed CLb value for the i-th entry
 
double CLbError (int index) const
 return the observed CLb value for the i-th entry
 
double CLs (int index) const
 return the observed CLb value for the i-th entry
 
double CLsError (int index) const
 return the observed CLb value for the i-th entry
 
double CLsplusb (int index) const
 return the observed CLsplusb value for the i-th entry
 
double CLsplusbError (int index) const
 return the observed CLsplusb value for the i-th entry
 
int ExclusionCleanup ()
 remove points that appear to have failed.
 
int FindIndex (double xvalue) const
 find the index corresponding at the poi value xvalue If no points is found return -1 Note that a tolerance is used of 10^-12 to find the closest point
 
double FindInterpolatedLimit (double target, bool lowSearch=false, double xmin=1, double xmax=0)
 interpolate to find a limit value Use a linear or a spline interpolation depending on the interpolation option
 
SamplingDistributionGetAltTestStatDist (int index) const
 
SamplingDistributionGetBackgroundTestStatDist (int index) const
 get the background test statistic distribution
 
double GetExpectedLowerLimit (double nsig=0, const char *opt="") const
 get Limit value corresponding at the desired nsigma level (0) is median -1 sigma is 1 sigma
 
SamplingDistributionGetExpectedPValueDist (int index) const
 return expected distribution of p-values (Cls or Clsplusb)
 
double GetExpectedUpperLimit (double nsig=0, const char *opt="") const
 get Limit value corresponding at the desired nsigma level (0) is median -1 sigma is 1 sigma
 
InterpolOption_t GetInterpolationOption () const
 
HypoTestResultGetLastResult () const
 
double GetLastXValue () const
 
double GetLastYError () const
 
double GetLastYValue () const
 
SamplingDistributionGetLowerLimitDistribution () const
 get expected lower limit distributions implemented using interpolation The size for the sampling distribution is given (by default is given by the average number of toy/point)
 
SamplingDistributionGetNullTestStatDist (int index) const
 same in terms of alt and null
 
HypoTestResultGetResult (int index) const
 return a pointer to the i^th result object
 
SamplingDistributionGetSignalAndBackgroundTestStatDist (int index) const
 get the signal and background test statistic distribution
 
SamplingDistributionGetUpperLimitDistribution () const
 get expected upper limit distributions implemented using interpolation
 
double GetXValue (int index) const
 function to return the value of the parameter of interest for the i^th entry in the results
 
double GetYError (int index) const
 function to return the estimated error on the value of the confidence level for the i^th entry in the results
 
double GetYValue (int index) const
 function to return the value of the confidence level for the i^th entry in the results
 
bool IsOneSided () const
 query if one sided result
 
bool IsTwoSided () const
 query if two sided result
 
Double_t LowerLimit ()
 lower and upper bound of the confidence interval (to get upper/lower limits, multiply the size( = 1-confidence level ) by 2
 
Double_t LowerLimitEstimatedError ()
 rough estimation of the error on the computed bound of the confidence interval Estimate of lower limit error function evaluates only a rough error on the lower limit.
 
HypoTestInverterResultoperator= (const HypoTestInverterResult &other)
 operator =
 
void SetCLsCleanupThreshold (Double_t th)
 set CLs threshold for exclusion cleanup function
 
virtual void SetConfidenceLevel (Double_t cl)
 set the confidence level for the interval (eg. 0.95 for a 95% Confidence Interval)
 
void SetInterpolationOption (InterpolOption_t opt)
 set the interpolation option, linear (kLinear ) or spline (kSpline)
 
virtual void SetTestSize (Double_t size)
 set the size of the test (rate of Type I error) (eg. 0.05 for a 95% Confidence Interval)
 
Double_t UpperLimit ()
 
Double_t UpperLimitEstimatedError ()
 Estimate of lower limit error function evaluates only a rough error on the lower limit.
 
void UseCLs (bool on=true)
 flag to switch between using CLsb (default) or CLs as confidence level
 
- Public Member Functions inherited from RooStats::SimpleInterval
 SimpleInterval (const char *name, const RooRealVar &var, Double_t lower, Double_t upper, Double_t cl)
 Alternate constructor.
 
 SimpleInterval (const char *name=0)
 Default constructor.
 
 SimpleInterval (const SimpleInterval &other, const char *name)
 fParameters.add( other.fParameters );
 
virtual ~SimpleInterval ()
 Destructor.
 
Bool_t CheckParameters (const RooArgSet &) const
 check if parameters are correct (i.e. they are the POI of this interval)
 
virtual Double_t ConfidenceLevel () const
 return confidence level
 
virtual RooArgSetGetParameters () const
 return cloned list of parameters
 
virtual Bool_t IsInInterval (const RooArgSet &) const
 Method to determine if a parameter point is in the interval.
 
SimpleIntervaloperator= (const SimpleInterval &other)
 
- Public Member Functions inherited from RooStats::ConfInterval
 ConfInterval (const char *name=0)
 constructor given name and title
 
virtual ~ConfInterval ()
 destructor
 
ConfIntervaloperator= (const ConfInterval &other)
 operator=
 
- 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)
 
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

double fCLsCleanupThreshold
 
TList fExpPValues
 list of HypoTestResult for each point
 
bool fFittedLowerLimit
 
bool fFittedUpperLimit
 
bool fInterpolateLowerLimit
 two sided scan (look for lower/upper limit)
 
bool fInterpolateUpperLimit
 
InterpolOption_t fInterpolOption
 
bool fIsTwoSided
 
double fLowerLimitError
 interpolation option (linear or spline)
 
double fUpperLimitError
 
bool fUseCLs
 
std::vector< doublefXValues
 number of points used to build expected p-values
 
TList fYObjects
 
- Protected Attributes inherited from RooStats::SimpleInterval
Double_t fConfidenceLevel
 
Double_t fLowerLimit
 
RooArgSet fParameters
 
Double_t fUpperLimit
 
- Protected Attributes inherited from TNamed
TString fName
 
TString fTitle
 

Static Protected Attributes

static double fgAsymptoticMaxSigma = 5
 
static int fgAsymptoticNumPoints = 11
 max sigma value used to scan asymptotic expected p values
 

Private Member Functions

double CalculateEstimatedError (double target, bool lower=true, double xmin=1, double xmax=0)
 Return an error estimate on the upper(lower) limit.
 
int FindClosestPointIndex (double target, int mode=0, double xtarget=0)
 
double GetExpectedLimit (double nsig, bool lower, const char *opt="") const
 get expected limit (lower/upper) depending on the flag for asymptotic is a special case (the distribution is generated an step in sigma values) distinguish asymptotic looking at the hypotest results if option = "P" get expected limit using directly quantiles of p value distribution else (default) find expected limit by obtaining first a full limit distributions The last one is in general more correct
 
double GetGraphX (const TGraph &g, double y0, bool lowSearch, double &xmin, double &xmax) const
 return the X value of the given graph for the target value y0 the graph is evaluated using linear interpolation by default.
 
double GetGraphX (const TGraph &g, double y0, bool lowSearch=true) const
 
SamplingDistributionGetLimitDistribution (bool lower) const
 get the limit distribution (lower/upper depending on the flag) by interpolating the expected p values for each point
 

Friends

class HypoTestInverter
 list of expected sampling distribution for each point
 
class HypoTestInverterOriginal
 
class HypoTestInverterPlot
 

Additional Inherited Members

- Static Public Member Functions inherited from TObject
static Long_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/HypoTestInverterResult.h>

Inheritance diagram for RooStats::HypoTestInverterResult:
[legend]

Member Enumeration Documentation

◆ InterpolOption_t

Enumerator
kLinear 
kSpline 

Definition at line 162 of file HypoTestInverterResult.h.

Constructor & Destructor Documentation

◆ HypoTestInverterResult() [1/3]

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

default constructor

Definition at line 58 of file HypoTestInverterResult.cxx.

◆ HypoTestInverterResult() [2/3]

HypoTestInverterResult::HypoTestInverterResult ( const char *  name,
const RooRealVar scannedVariable,
double  cl 
)

constructor

Definition at line 152 of file HypoTestInverterResult.cxx.

◆ HypoTestInverterResult() [3/3]

HypoTestInverterResult::HypoTestInverterResult ( const HypoTestInverterResult other,
const char *  name 
)

copy constructor

Definition at line 81 of file HypoTestInverterResult.cxx.

◆ ~HypoTestInverterResult()

HypoTestInverterResult::~HypoTestInverterResult ( )
virtual

destructor

Definition at line 181 of file HypoTestInverterResult.cxx.

Member Function Documentation

◆ Add() [1/2]

bool HypoTestInverterResult::Add ( const HypoTestInverterResult otherResult)

merge with the content of another HypoTestInverterResult object

Merge this HypoTestInverterResult with another HypoTestInverterResult passed as argument The merge is done by combining the HypoTestResult when the same point value exist in both results.

If results exist at different points these are added in the new result NOTE: Merging of the expected p-values obtained with pseudo-data. When expected p-values exist in the result (i.e. when rebuild option is used when getting the expected limit distribution in the HYpoTestInverter) then the expected p-values are also merged. This is equivalent at merging the pseudo-data. However there can be an inconsistency if the expected p-values have been obtained with different toys. In this case the merge is done but a warning message is printed.

Definition at line 321 of file HypoTestInverterResult.cxx.

◆ Add() [2/2]

bool HypoTestInverterResult::Add ( Double_t  x,
const HypoTestResult result 
)

add the result of a single point (an HypoTestRsult)

Add a single point result (an HypoTestResult)

Definition at line 410 of file HypoTestInverterResult.cxx.

◆ ArraySize()

int RooStats::HypoTestInverterResult::ArraySize ( ) const
inline

number of entries in the results array

Definition at line 94 of file HypoTestInverterResult.h.

◆ CalculateEstimatedError()

Double_t HypoTestInverterResult::CalculateEstimatedError ( double  target,
bool  lower = true,
double  xmin = 1,
double  xmax = 0 
)
private

Return an error estimate on the upper(lower) limit.

This is the error on either CLs or CLsplusb divided by an estimate of the slope at this point.

Definition at line 974 of file HypoTestInverterResult.cxx.

◆ CLb()

double HypoTestInverterResult::CLb ( int  index) const

return the observed CLb value for the i-th entry

function to return the observed CLb value for the i-th entry

Definition at line 479 of file HypoTestInverterResult.cxx.

◆ CLbError()

double HypoTestInverterResult::CLbError ( int  index) const

return the observed CLb value for the i-th entry

function to return the error on the observed CLb value for the i-th entry

Definition at line 515 of file HypoTestInverterResult.cxx.

◆ CLs()

double HypoTestInverterResult::CLs ( int  index) const

return the observed CLb value for the i-th entry

function to return the observed CLs value for the i-th entry

Definition at line 503 of file HypoTestInverterResult.cxx.

◆ CLsError()

double HypoTestInverterResult::CLsError ( int  index) const

return the observed CLb value for the i-th entry

function to return the error on the observed CLs value for the i-th entry

Definition at line 539 of file HypoTestInverterResult.cxx.

◆ CLsplusb()

double HypoTestInverterResult::CLsplusb ( int  index) const

return the observed CLsplusb value for the i-th entry

function to return the observed CLs+b value for the i-th entry

Definition at line 491 of file HypoTestInverterResult.cxx.

◆ CLsplusbError()

double HypoTestInverterResult::CLsplusbError ( int  index) const

return the observed CLsplusb value for the i-th entry

function to return the error on the observed CLs+b value for the i-th entry

Definition at line 527 of file HypoTestInverterResult.cxx.

◆ ExclusionCleanup()

int HypoTestInverterResult::ExclusionCleanup ( )

remove points that appear to have failed.

Remove problematic points from this result.

This function can be used to clean up a result that has failed fits, spiking CLs or similar problems. It removes

  • Points where CLs is not falling monotonously. These may result from a lack of numerical precision.
  • Points where CLs spikes to more than 0.999.
  • Points with very low CLs. These are not needed to run the inverter, which speeds up the process.
  • Points where CLs < 0. These occur when fits fail.

Definition at line 200 of file HypoTestInverterResult.cxx.

◆ FindClosestPointIndex()

int HypoTestInverterResult::FindClosestPointIndex ( double  target,
int  mode = 0,
double  xtarget = 0 
)
private
  • if mode = 0 find closest point to target in Y, the object closest to the target which is 3 sigma from the target and has smaller error
  • if mode = 1 find 2 closest point to target in X and between these two take the one closer to the target
  • if mode = 2 as in mode = 1 but return the lower point not the closest one
  • if mode = 3 as in mode = 1 but return the upper point not the closest one

Definition at line 885 of file HypoTestInverterResult.cxx.

◆ FindIndex()

int HypoTestInverterResult::FindIndex ( double  xvalue) const

find the index corresponding at the poi value xvalue If no points is found return -1 Note that a tolerance is used of 10^-12 to find the closest point

Definition at line 566 of file HypoTestInverterResult.cxx.

◆ FindInterpolatedLimit()

double HypoTestInverterResult::FindInterpolatedLimit ( double  target,
bool  lowSearch = false,
double  xmin = 1,
double  xmax = 0 
)

interpolate to find a limit value Use a linear or a spline interpolation depending on the interpolation option

Definition at line 712 of file HypoTestInverterResult.cxx.

◆ GetAltTestStatDist()

SamplingDistribution * RooStats::HypoTestInverterResult::GetAltTestStatDist ( int  index) const
inline

Definition at line 140 of file HypoTestInverterResult.h.

◆ GetBackgroundTestStatDist()

SamplingDistribution * HypoTestInverterResult::GetBackgroundTestStatDist ( int  index) const

get the background test statistic distribution

Definition at line 1108 of file HypoTestInverterResult.cxx.

◆ GetExpectedLimit()

double HypoTestInverterResult::GetExpectedLimit ( double  nsig,
bool  lower,
const char *  opt = "" 
) const
private

get expected limit (lower/upper) depending on the flag for asymptotic is a special case (the distribution is generated an step in sigma values) distinguish asymptotic looking at the hypotest results if option = "P" get expected limit using directly quantiles of p value distribution else (default) find expected limit by obtaining first a full limit distributions The last one is in general more correct

Definition at line 1314 of file HypoTestInverterResult.cxx.

◆ GetExpectedLowerLimit()

double HypoTestInverterResult::GetExpectedLowerLimit ( double  nsig = 0,
const char *  opt = "" 
) const

get Limit value corresponding at the desired nsigma level (0) is median -1 sigma is 1 sigma

Get the expected lower limit nsig is used to specify which expected value of the UpperLimitDistribution For example.

  • nsig = 0 (default value) returns the expected value
  • nsig = -1 returns the lower band value at -1 sigma
  • nsig + 1 return the upper value
  • opt = "" (default) : compute limit by interpolating all the p values, find the corresponding limit distribution and then find the quantiles in the limit distribution ioption = "P" is the method used for plotting. One Finds the corresponding nsig quantile in the p values and then interpolates them

Definition at line 1283 of file HypoTestInverterResult.cxx.

◆ GetExpectedPValueDist()

SamplingDistribution * HypoTestInverterResult::GetExpectedPValueDist ( int  index) const

return expected distribution of p-values (Cls or Clsplusb)

get the expected p-value distribution at the scanned point index

Definition at line 1127 of file HypoTestInverterResult.cxx.

◆ GetExpectedUpperLimit()

double HypoTestInverterResult::GetExpectedUpperLimit ( double  nsig = 0,
const char *  opt = "" 
) const

get Limit value corresponding at the desired nsigma level (0) is median -1 sigma is 1 sigma

Get the expected upper limit nsig is used to specify which expected value of the UpperLimitDistribution For example.

  • nsig = 0 (default value) returns the expected value
  • nsig = -1 returns the lower band value at -1 sigma
  • nsig + 1 return the upper value
  • opt is an option specifying the type of method used for computing the upper limit
  • opt = "" (default) : compute limit by interpolating all the p values, find the corresponding limit distribution and then find the quantiles in the limit distribution ioption = "P" is the method used for plotting. One Finds the corresponding nsig quantile in the p values and then interpolates them

Definition at line 1301 of file HypoTestInverterResult.cxx.

◆ GetGraphX() [1/2]

double HypoTestInverterResult::GetGraphX ( const TGraph graph,
double  y0,
bool  lowSearch,
double axmin,
double axmax 
) const
private

return the X value of the given graph for the target value y0 the graph is evaluated using linear interpolation by default.

if option = "S" a TSpline3 is used

Definition at line 583 of file HypoTestInverterResult.cxx.

◆ GetGraphX() [2/2]

double RooStats::HypoTestInverterResult::GetGraphX ( const TGraph g,
double  y0,
bool  lowSearch = true 
) const
inlineprivate

Definition at line 181 of file HypoTestInverterResult.h.

◆ GetInterpolationOption()

InterpolOption_t RooStats::HypoTestInverterResult::GetInterpolationOption ( ) const
inline

Definition at line 167 of file HypoTestInverterResult.h.

◆ GetLastResult()

HypoTestResult * RooStats::HypoTestInverterResult::GetLastResult ( ) const
inline

Definition at line 91 of file HypoTestInverterResult.h.

◆ GetLastXValue()

double RooStats::HypoTestInverterResult::GetLastXValue ( ) const
inline

Definition at line 87 of file HypoTestInverterResult.h.

◆ GetLastYError()

double RooStats::HypoTestInverterResult::GetLastYError ( ) const
inline

Definition at line 89 of file HypoTestInverterResult.h.

◆ GetLastYValue()

double RooStats::HypoTestInverterResult::GetLastYValue ( ) const
inline

Definition at line 85 of file HypoTestInverterResult.h.

◆ GetLimitDistribution()

SamplingDistribution * HypoTestInverterResult::GetLimitDistribution ( bool  lower) const
private

get the limit distribution (lower/upper depending on the flag) by interpolating the expected p values for each point

Definition at line 1183 of file HypoTestInverterResult.cxx.

◆ GetLowerLimitDistribution()

SamplingDistribution * RooStats::HypoTestInverterResult::GetLowerLimitDistribution ( ) const
inline

get expected lower limit distributions implemented using interpolation The size for the sampling distribution is given (by default is given by the average number of toy/point)

Definition at line 147 of file HypoTestInverterResult.h.

◆ GetNullTestStatDist()

SamplingDistribution * RooStats::HypoTestInverterResult::GetNullTestStatDist ( int  index) const
inline

same in terms of alt and null

Definition at line 137 of file HypoTestInverterResult.h.

◆ GetResult()

HypoTestResult * HypoTestInverterResult::GetResult ( int  index) const

return a pointer to the i^th result object

get the HypoTestResult object at the given index point

Definition at line 551 of file HypoTestInverterResult.cxx.

◆ GetSignalAndBackgroundTestStatDist()

SamplingDistribution * HypoTestInverterResult::GetSignalAndBackgroundTestStatDist ( int  index) const

get the signal and background test statistic distribution

Definition at line 1118 of file HypoTestInverterResult.cxx.

◆ GetUpperLimitDistribution()

SamplingDistribution * RooStats::HypoTestInverterResult::GetUpperLimitDistribution ( ) const
inline

get expected upper limit distributions implemented using interpolation

Definition at line 151 of file HypoTestInverterResult.h.

◆ GetXValue()

double HypoTestInverterResult::GetXValue ( int  index) const

function to return the value of the parameter of interest for the i^th entry in the results

Definition at line 432 of file HypoTestInverterResult.cxx.

◆ GetYError()

double HypoTestInverterResult::GetYError ( int  index) const

function to return the estimated error on the value of the confidence level for the i^th entry in the results

Definition at line 462 of file HypoTestInverterResult.cxx.

◆ GetYValue()

double HypoTestInverterResult::GetYValue ( int  index) const

function to return the value of the confidence level for the i^th entry in the results

Definition at line 445 of file HypoTestInverterResult.cxx.

◆ IsOneSided()

bool RooStats::HypoTestInverterResult::IsOneSided ( ) const
inline

query if one sided result

Definition at line 111 of file HypoTestInverterResult.h.

◆ IsTwoSided()

bool RooStats::HypoTestInverterResult::IsTwoSided ( ) const
inline

query if two sided result

Definition at line 113 of file HypoTestInverterResult.h.

◆ LowerLimit()

Double_t HypoTestInverterResult::LowerLimit ( )
virtual

lower and upper bound of the confidence interval (to get upper/lower limits, multiply the size( = 1-confidence level ) by 2

Reimplemented from RooStats::SimpleInterval.

Definition at line 940 of file HypoTestInverterResult.cxx.

◆ LowerLimitEstimatedError()

Double_t HypoTestInverterResult::LowerLimitEstimatedError ( )

rough estimation of the error on the computed bound of the confidence interval Estimate of lower limit error function evaluates only a rough error on the lower limit.

need to have compute first lower limit

Be careful when using this estimation

Definition at line 1087 of file HypoTestInverterResult.cxx.

◆ operator=()

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

operator =

Definition at line 111 of file HypoTestInverterResult.cxx.

◆ SetCLsCleanupThreshold()

void RooStats::HypoTestInverterResult::SetCLsCleanupThreshold ( Double_t  th)
inline

set CLs threshold for exclusion cleanup function

Definition at line 105 of file HypoTestInverterResult.h.

◆ SetConfidenceLevel()

virtual void RooStats::HypoTestInverterResult::SetConfidenceLevel ( Double_t  cl)
inlinevirtual

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

Reimplemented from RooStats::SimpleInterval.

Definition at line 102 of file HypoTestInverterResult.h.

◆ SetInterpolationOption()

void RooStats::HypoTestInverterResult::SetInterpolationOption ( InterpolOption_t  opt)
inline

set the interpolation option, linear (kLinear ) or spline (kSpline)

Definition at line 165 of file HypoTestInverterResult.h.

◆ SetTestSize()

virtual void RooStats::HypoTestInverterResult::SetTestSize ( Double_t  size)
inlinevirtual

set the size of the test (rate of Type I error) (eg. 0.05 for a 95% Confidence Interval)

Definition at line 99 of file HypoTestInverterResult.h.

◆ UpperLimit()

Double_t HypoTestInverterResult::UpperLimit ( )
virtual

Reimplemented from RooStats::SimpleInterval.

Definition at line 956 of file HypoTestInverterResult.cxx.

◆ UpperLimitEstimatedError()

Double_t HypoTestInverterResult::UpperLimitEstimatedError ( )

Estimate of lower limit error function evaluates only a rough error on the lower limit.

Be careful when using this estimation

Definition at line 1097 of file HypoTestInverterResult.cxx.

◆ UseCLs()

void RooStats::HypoTestInverterResult::UseCLs ( bool  on = true)
inline

flag to switch between using CLsb (default) or CLs as confidence level

Definition at line 108 of file HypoTestInverterResult.h.

Friends And Related Symbol Documentation

◆ HypoTestInverter

friend class HypoTestInverter
friend

list of expected sampling distribution for each point

Definition at line 210 of file HypoTestInverterResult.h.

◆ HypoTestInverterOriginal

friend class HypoTestInverterOriginal
friend

Definition at line 212 of file HypoTestInverterResult.h.

◆ HypoTestInverterPlot

friend class HypoTestInverterPlot
friend

Definition at line 211 of file HypoTestInverterResult.h.

Member Data Documentation

◆ fCLsCleanupThreshold

double RooStats::HypoTestInverterResult::fCLsCleanupThreshold
protected

Definition at line 200 of file HypoTestInverterResult.h.

◆ fExpPValues

TList RooStats::HypoTestInverterResult::fExpPValues
protected

list of HypoTestResult for each point

Definition at line 208 of file HypoTestInverterResult.h.

◆ fFittedLowerLimit

bool RooStats::HypoTestInverterResult::fFittedLowerLimit
protected

Definition at line 193 of file HypoTestInverterResult.h.

◆ fFittedUpperLimit

bool RooStats::HypoTestInverterResult::fFittedUpperLimit
protected

Definition at line 194 of file HypoTestInverterResult.h.

◆ fgAsymptoticMaxSigma

double HypoTestInverterResult::fgAsymptoticMaxSigma = 5
staticprotected

Definition at line 202 of file HypoTestInverterResult.h.

◆ fgAsymptoticNumPoints

int HypoTestInverterResult::fgAsymptoticNumPoints = 11
staticprotected

max sigma value used to scan asymptotic expected p values

Definition at line 203 of file HypoTestInverterResult.h.

◆ fInterpolateLowerLimit

bool RooStats::HypoTestInverterResult::fInterpolateLowerLimit
protected

two sided scan (look for lower/upper limit)

Definition at line 191 of file HypoTestInverterResult.h.

◆ fInterpolateUpperLimit

bool RooStats::HypoTestInverterResult::fInterpolateUpperLimit
protected

Definition at line 192 of file HypoTestInverterResult.h.

◆ fInterpolOption

InterpolOption_t RooStats::HypoTestInverterResult::fInterpolOption
protected

Definition at line 195 of file HypoTestInverterResult.h.

◆ fIsTwoSided

bool RooStats::HypoTestInverterResult::fIsTwoSided
protected

Definition at line 190 of file HypoTestInverterResult.h.

◆ fLowerLimitError

double RooStats::HypoTestInverterResult::fLowerLimitError
protected

interpolation option (linear or spline)

Definition at line 197 of file HypoTestInverterResult.h.

◆ fUpperLimitError

double RooStats::HypoTestInverterResult::fUpperLimitError
protected

Definition at line 198 of file HypoTestInverterResult.h.

◆ fUseCLs

bool RooStats::HypoTestInverterResult::fUseCLs
protected

Definition at line 189 of file HypoTestInverterResult.h.

◆ fXValues

std::vector<double> RooStats::HypoTestInverterResult::fXValues
protected

number of points used to build expected p-values

Definition at line 205 of file HypoTestInverterResult.h.

◆ fYObjects

TList RooStats::HypoTestInverterResult::fYObjects
protected

Definition at line 207 of file HypoTestInverterResult.h.

Libraries for RooStats::HypoTestInverterResult:

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