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Reference Guide
RooStats::ToyMCImportanceSampler Class Reference

ToyMCImportanceSampler is an extension of the ToyMCSampler for Importance Sampling.

Implementation based on a work by Cranmer, Kreiss, Read (in Preparation)

Definition at line 22 of file ToyMCImportanceSampler.h.

Public Member Functions

 ToyMCImportanceSampler ()
 
 ToyMCImportanceSampler (TestStatistic &ts, Int_t ntoys)
 
 ~ToyMCImportanceSampler () override
 
void AddImportanceDensity (RooAbsPdf *p, const RooArgSet *s)
 For importance sampling with multiple densities/snapshots: This is used to check the current Likelihood against Likelihoods from other importance densities apart from the one given as importance snapshot. More...
 
void AddNullDensity (RooAbsPdf *p, const RooArgSet *s=NULL)
 The pdf can be NULL in which case the density from SetPdf() is used. More...
 
int CreateImpDensitiesForOnePOIAdaptively (RooAbsPdf &pdf, const RooArgSet &allPOI, RooRealVar &poi, double nStdDevOverlap=0.5, double poiValueForBackground=0.0)
 poi has to be fitted beforehand. This function expects this to be the muhat value. More...
 
int CreateNImpDensitiesForOnePOI (RooAbsPdf &pdf, const RooArgSet &allPOI, RooRealVar &poi, int n, double poiValueForBackground=0.0)
 n is the number of importance densities More...
 
virtual RooAbsDataGenerateToyData (RooArgSet &paramPoint) const
 
virtual RooAbsDataGenerateToyData (RooArgSet &paramPoint, double &weight) const
 
RooAbsDataGenerateToyData (RooArgSet &paramPoint, double &weight) const override
 
virtual RooAbsDataGenerateToyData (RooArgSet &paramPoint, double &weight, RooAbsPdf &pdf) const
 generates toy data with weight More...
 
virtual RooAbsDataGenerateToyData (RooArgSet &paramPoint, double &weight, std::vector< double > &impNLLs, double &nullNLL) const
 
virtual RooAbsDataGenerateToyData (RooArgSet &paramPoint, RooAbsPdf &pdf) const
 generates toy data without weight More...
 
virtual RooAbsDataGenerateToyData (std::vector< double > &weights) const
 
virtual RooAbsDataGenerateToyData (std::vector< double > &weights, std::vector< double > &nullNLLs, std::vector< double > &impNLLs) const
 This method generates a toy data set for importance sampling for the given parameter point taking global observables into account. More...
 
RooDataSetGetSamplingDistributionsSingleWorker (RooArgSet &paramPoint) override
 overwrite GetSamplingDistributionsSingleWorker(paramPoint) with a version that loops over nulls and importance densities, but calls the parent ToyMCSampler::GetSamplingDistributionsSingleWorker(paramPoint). More...
 
TClassIsA () const override
 
void SetApplyVeto (bool b=true)
 When set to true, this sets the weight of all toys to zero that do not have the largest likelihood under the density it was generated compared to the other densities. More...
 
virtual void SetConditionalObservables (const RooArgSet &set)
 set the conditional observables which will be used when creating the NLL so the pdf's will not be normalized on the conditional observables when computing the NLL Since the class use a NLL we need to set the conditional observables if they exist in the model More...
 
void SetDensityToGenerateFromByIndex (unsigned int i, bool fromNull=false)
 specifies the pdf to sample from More...
 
void SetEqualNumToysPerDensity (void)
 
void SetExpIncreasingNumToysPerDensity (void)
 
void SetParametersForTestStat (const RooArgSet &nullpoi) override
 overwrite from ToyMCSampler More...
 
void SetPdf (RooAbsPdf &pdf) override
 overwrite from ToyMCSampler More...
 
void SetReuseNLL (bool r=true)
 
void Streamer (TBuffer &) override
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 
- Public Member Functions inherited from RooStats::ToyMCSampler
 ToyMCSampler ()
 Proof constructor. Do not use. More...
 
 ToyMCSampler (TestStatistic &ts, Int_t ntoys)
 
 ~ToyMCSampler () override
 
virtual void AddTestStatistic (TestStatistic *t=NULL)
 The pdf can be NULL in which case the density from SetPdf() is used. More...
 
virtual SamplingDistributionAppendSamplingDistribution (RooArgSet &allParameters, SamplingDistribution *last, Int_t additionalMC)
 Extended interface to append to sampling distribution more samples. More...
 
bool CheckConfig (void)
 Checks for sufficient information to do a GetSamplingDistribution(...). More...
 
double ConfidenceLevel () const override
 Get the Confidence level for the test. More...
 
virtual RooArgListEvaluateAllTestStatistics (RooAbsData &data, const RooArgSet &poi)
 Evaluate all test statistics, returning result and any detailed output. More...
 
double EvaluateTestStatistic (RooAbsData &data, RooArgSet &nullPOI) override
 Main interface to evaluate the test statistic on a dataset. More...
 
virtual double EvaluateTestStatistic (RooAbsData &data, RooArgSet &nullPOI, int i)
 Main interface to evaluate the test statistic on a dataset. More...
 
virtual void GenerateGlobalObservables (RooAbsPdf &pdf) const
 generate global observables More...
 
virtual RooAbsDataGenerateToyData (RooArgSet &paramPoint) const
 
virtual RooAbsDataGenerateToyData (RooArgSet &paramPoint, double &weight) const
 
virtual RooAbsDataGenerateToyData (RooArgSet &paramPoint, double &weight, RooAbsPdf &pdf) const
 generates toy data with weight More...
 
virtual RooAbsDataGenerateToyData (RooArgSet &paramPoint, RooAbsPdf &pdf) const
 generates toy data without weight More...
 
virtual Int_t GetNToys (void)
 
std::string GetSamplingDistName (void)
 
SamplingDistributionGetSamplingDistribution (RooArgSet &paramPoint) override
 main interface More...
 
virtual RooDataSetGetSamplingDistributions (RooArgSet &paramPoint)
 Use for serial and parallel runs. More...
 
virtual RooDataSetGetSamplingDistributionsSingleWorker (RooArgSet &paramPoint)
 This is the main function for serial runs. More...
 
virtual TestStatisticGetTestStatistic (unsigned int i) const
 
TestStatisticGetTestStatistic (void) const override
 Get the TestStatistic. More...
 
void Initialize (RooAbsArg &, RooArgSet &, RooArgSet &) override
 Common Initialization. More...
 
TClassIsA () const override
 
virtual void SetAsimovNuisancePar (bool i=true)
 
void SetConfidenceLevel (double cl) override
 set the confidence level for the interval (eg. 0.95 for a 95% Confidence Interval) More...
 
virtual void SetExpectedNuisancePar (bool i=true)
 
void SetGenerateAutoBinned (bool autoBinned=true)
 set auto binned generation (=> see RooFit::AutoBinned() option) More...
 
void SetGenerateBinned (bool binned=true)
 control to use bin data generation (=> see RooFit::AllBinned() option) More...
 
void SetGenerateBinnedTag (const char *binnedTag="")
 name of the tag for individual components to be generated binned (=> see RooFit::GenBinned() option) More...
 
void SetGlobalObservables (const RooArgSet &o) override
 specify the conditional observables More...
 
void SetMaxToys (double t)
 This option forces a maximum number of total toys. More...
 
virtual void SetNEventsPerToy (const Int_t nevents)
 Forces the generation of exactly n events even for extended PDFs. More...
 
virtual void SetNToys (const Int_t ntoy)
 
void SetNuisanceParameters (const RooArgSet &np) override
 specify the nuisance parameters (eg. the rest of the parameters) More...
 
void SetObservables (const RooArgSet &o) override
 specify the observables in the dataset (needed to evaluate the test statistic) More...
 
void SetParametersForTestStat (const RooArgSet &nullpoi) override
 Set the Pdf, add to the the workspace if not already there. More...
 
void SetPdf (RooAbsPdf &pdf) override
 Set the Pdf, add to the the workspace if not already there. More...
 
void SetPriorNuisance (RooAbsPdf *pdf) override
 How to randomize the prior. Set to NULL to deactivate randomization. More...
 
void SetProofConfig (ProofConfig *pc=NULL)
 calling with argument or NULL deactivates proof More...
 
void SetProtoData (const RooDataSet *d)
 
void SetSamplingDistName (const char *name) override
 Set the name of the sampling distribution used for plotting. More...
 
void SetTestSize (double size) override
 set the size of the test (rate of Type I error) ( Eg. 0.05 for a 95% Confidence Interval) More...
 
void SetTestStatistic (TestStatistic *t) override
 Set the TestStatistic (want the argument to be a function of the data & parameter points. More...
 
virtual void SetTestStatistic (TestStatistic *testStatistic, unsigned int i)
 Set the TestStatistic (want the argument to be a function of the data & parameter points. More...
 
void SetToysBothTails (double toys, double low_threshold, double high_threshold)
 
void SetToysLeftTail (double toys, double threshold)
 
void SetToysRightTail (double toys, double threshold)
 
void SetUseMultiGen (bool flag)
 
void Streamer (TBuffer &) override
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 
- Public Member Functions inherited from RooStats::TestStatSampler
virtual ~TestStatSampler ()
 
virtual double ConfidenceLevel () const =0
 Get the Confidence level for the test. More...
 
virtual double EvaluateTestStatistic (RooAbsData &data, RooArgSet &paramsOfInterest)=0
 Main interface to evaluate the test statistic on a dataset. More...
 
virtual SamplingDistributionGetSamplingDistribution (RooArgSet &paramsOfInterest)=0
 Main interface to get a ConfInterval, pure virtual. More...
 
virtual TestStatisticGetTestStatistic () const =0
 Get the TestStatistic. More...
 
virtual void Initialize (RooAbsArg &testStatistic, RooArgSet &paramsOfInterest, RooArgSet &nuisanceParameters)=0
 Common Initialization. More...
 
virtual TClassIsA () const
 
virtual void SetConfidenceLevel (double cl)=0
 set the confidence level for the interval (eg. 0.95 for a 95% Confidence Interval) More...
 
virtual void SetGlobalObservables (const RooArgSet &)=0
 specify the conditional observables More...
 
virtual void SetNuisanceParameters (const RooArgSet &)=0
 specify the nuisance parameters (eg. the rest of the parameters) More...
 
virtual void SetObservables (const RooArgSet &)=0
 specify the observables in the dataset (needed to evaluate the test statistic) More...
 
virtual void SetParametersForTestStat (const RooArgSet &)=0
 specify the values of parameters used when evaluating test statistic More...
 
virtual void SetPdf (RooAbsPdf &)=0
 Set the Pdf, add to the the workspace if not already there. More...
 
virtual void SetPriorNuisance (RooAbsPdf *)=0
 How to randomize the prior. Set to NULL to deactivate randomization. More...
 
virtual void SetSamplingDistName (const char *name)=0
 Set the name of the sampling distribution used for plotting. More...
 
virtual void SetTestSize (double size)=0
 set the size of the test (rate of Type I error) ( Eg. 0.05 for a 95% Confidence Interval) More...
 
virtual void SetTestStatistic (TestStatistic *testStatistic)=0
 Set the TestStatistic (want the argument to be a function of the data & parameter points. More...
 
virtual void Streamer (TBuffer &)
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 

Static Public Member Functions

static TClassClass ()
 
static const char * Class_Name ()
 
static Version_t Class_Version ()
 
static const char * DeclFileName ()
 
- Static Public Member Functions inherited from RooStats::ToyMCSampler
static TClassClass ()
 
static const char * Class_Name ()
 
static Version_t Class_Version ()
 
static const char * DeclFileName ()
 
static void SetAlwaysUseMultiGen (bool flag)
 
- Static Public Member Functions inherited from RooStats::TestStatSampler
static TClassClass ()
 
static const char * Class_Name ()
 
static Version_t Class_Version ()
 
static const char * DeclFileName ()
 

Protected Member Functions

void ClearCache () override
 helper method for clearing the cache More...
 
- Protected Member Functions inherited from RooStats::ToyMCSampler
virtual void ClearCache ()
 helper method for clearing the cache More...
 
const RooArgListEvaluateAllTestStatistics (RooAbsData &data, const RooArgSet &poi, DetailedOutputAggregator &detOutAgg)
 
RooAbsDataGenerate (RooAbsPdf &pdf, RooArgSet &observables, const RooDataSet *protoData=NULL, int forceEvents=0) const
 helper for GenerateToyData More...
 

Protected Attributes

bool fApplyVeto
 
RooArgSet fConditionalObs
 set of conditional observables More...
 
bool fGenerateFromNull
 
std::vector< RooAbsReal * > fImpNLLs
 ! More...
 
std::vector< RooAbsPdf * > fImportanceDensities
 
std::vector< const RooArgSet * > fImportanceSnapshots
 
unsigned int fIndexGenDensity
 
std::vector< RooAbsPdf * > fNullDensities
 support multiple null densities More...
 
std::vector< RooAbsReal * > fNullNLLs
 ! More...
 
std::vector< const RooArgSet * > fNullSnapshots
 
bool fReuseNLL
 
toysStrategies fToysStrategy
 
- Protected Attributes inherited from RooStats::ToyMCSampler
std::unique_ptr< RooArgSet_allVars
 ! More...
 
std::unique_ptr< RooAbsPdf::GenSpec_gs1
 ! GenSpec #1 More...
 
std::unique_ptr< RooAbsPdf::GenSpec_gs2
 ! GenSpec #2 More...
 
std::unique_ptr< RooAbsPdf::GenSpec_gs3
 ! GenSpec #3 More...
 
std::unique_ptr< RooAbsPdf::GenSpec_gs4
 ! GenSpec #4 More...
 
std::vector< std::unique_ptr< RooAbsPdf::GenSpec > > _gsList
 ! More...
 
std::vector< std::unique_ptr< RooArgSet > > _obsList
 ! More...
 
std::vector< RooAbsPdf * > _pdfList
 ! We don't own those objects More...
 
double fAdaptiveHighLimit
 
double fAdaptiveLowLimit
 tails More...
 
bool fExpectedNuisancePar
 whether to use expectation values for nuisance parameters (ie Asimov data set) More...
 
bool fGenerateAutoBinned
 
bool fGenerateBinned
 
TString fGenerateBinnedTag
 
const RooArgSetfGlobalObservables
 
double fMaxToys
 maximum no of toys (taking weights into account, therefore double) More...
 
Int_t fNEvents
 number of events per toy (may be ignored depending on settings) More...
 
Int_t fNToys
 number of toys to generate More...
 
NuisanceParametersSamplerfNuisanceParametersSampler
 ! More...
 
const RooArgSetfNuisancePars
 
const RooArgSetfObservables
 
std::unique_ptr< const RooArgSetfParametersForTestStat
 
RooAbsPdffPdf
 densities, snapshots, and test statistics to reweight to More...
 
RooAbsPdffPriorNuisance
 prior pdf for nuisance parameters More...
 
ProofConfigfProofConfig
 ! More...
 
const RooDataSetfProtoData
 in dev More...
 
std::string fSamplingDistName
 name of the model More...
 
double fSize
 
std::vector< TestStatistic * > fTestStatistics
 
double fToysInTails
 minimum no of toys in tails for adaptive sampling (taking weights into account, therefore double) Default: 0.0 which means no adaptive sampling More...
 
bool fUseMultiGen
 Use PrepareMultiGen? More...
 

Additional Inherited Members

- Static Protected Attributes inherited from RooStats::ToyMCSampler
static bool fgAlwaysUseMultiGen = false
 Use PrepareMultiGen always. More...
 

#include <RooStats/ToyMCImportanceSampler.h>

Inheritance diagram for RooStats::ToyMCImportanceSampler:
[legend]

Constructor & Destructor Documentation

◆ ToyMCImportanceSampler() [1/2]

RooStats::ToyMCImportanceSampler::ToyMCImportanceSampler ( )
inline

Definition at line 25 of file ToyMCImportanceSampler.h.

◆ ToyMCImportanceSampler() [2/2]

RooStats::ToyMCImportanceSampler::ToyMCImportanceSampler ( TestStatistic ts,
Int_t  ntoys 
)
inline

Definition at line 36 of file ToyMCImportanceSampler.h.

◆ ~ToyMCImportanceSampler()

RooStats::ToyMCImportanceSampler::~ToyMCImportanceSampler ( )
override

Definition at line 37 of file ToyMCImportanceSampler.cxx.

Member Function Documentation

◆ AddImportanceDensity()

void RooStats::ToyMCImportanceSampler::AddImportanceDensity ( RooAbsPdf p,
const RooArgSet s 
)
inline

For importance sampling with multiple densities/snapshots: This is used to check the current Likelihood against Likelihoods from other importance densities apart from the one given as importance snapshot.

The pdf can be NULL in which case the density from SetImportanceDensity() is used. The snapshot is also optional.

Definition at line 81 of file ToyMCImportanceSampler.h.

◆ AddNullDensity()

void RooStats::ToyMCImportanceSampler::AddNullDensity ( RooAbsPdf p,
const RooArgSet s = NULL 
)
inline

The pdf can be NULL in which case the density from SetPdf() is used.

The snapshot and TestStatistic is also optional.

Definition at line 102 of file ToyMCImportanceSampler.h.

◆ Class()

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

◆ Class_Name()

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

◆ Class_Version()

static Version_t RooStats::ToyMCImportanceSampler::Class_Version ( )
inlinestatic
Returns
Version of this class

Definition at line 197 of file ToyMCImportanceSampler.h.

◆ ClearCache()

void RooStats::ToyMCImportanceSampler::ClearCache ( void  )
overrideprotectedvirtual

helper method for clearing the cache

Reimplemented from RooStats::ToyMCSampler.

Definition at line 44 of file ToyMCImportanceSampler.cxx.

◆ CreateImpDensitiesForOnePOIAdaptively()

int RooStats::ToyMCImportanceSampler::CreateImpDensitiesForOnePOIAdaptively ( RooAbsPdf pdf,
const RooArgSet allPOI,
RooRealVar poi,
double  nStdDevOverlap = 0.5,
double  poiValueForBackground = 0.0 
)

poi has to be fitted beforehand. This function expects this to be the muhat value.

Definition at line 438 of file ToyMCImportanceSampler.cxx.

◆ CreateNImpDensitiesForOnePOI()

int RooStats::ToyMCImportanceSampler::CreateNImpDensitiesForOnePOI ( RooAbsPdf pdf,
const RooArgSet allPOI,
RooRealVar poi,
int  n,
double  poiValueForBackground = 0.0 
)

n is the number of importance densities

Definition at line 461 of file ToyMCImportanceSampler.cxx.

◆ DeclFileName()

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

Definition at line 197 of file ToyMCImportanceSampler.h.

◆ GenerateToyData() [1/8]

virtual RooAbsData * RooStats::ToyMCSampler::GenerateToyData ( RooArgSet paramPoint) const
inlinevirtual

Reimplemented from RooStats::ToyMCSampler.

Definition at line 109 of file ToyMCSampler.h.

◆ GenerateToyData() [2/8]

virtual RooAbsData * RooStats::ToyMCSampler::GenerateToyData ( RooArgSet paramPoint,
double weight 
) const
inlinevirtual

Reimplemented from RooStats::ToyMCSampler.

Definition at line 113 of file ToyMCSampler.h.

◆ GenerateToyData() [3/8]

RooAbsData * RooStats::ToyMCImportanceSampler::GenerateToyData ( RooArgSet paramPoint,
double weight 
) const
overridevirtual

Reimplemented from RooStats::ToyMCSampler.

Definition at line 135 of file ToyMCImportanceSampler.cxx.

◆ GenerateToyData() [4/8]

RooAbsData * RooStats::ToyMCSampler::GenerateToyData ( RooArgSet paramPoint,
double weight,
RooAbsPdf pdf 
) const
virtual

generates toy data with weight

This method generates a toy data set for the given parameter point taking global observables into account.

The values of the generated global observables remain in the pdf's variables. They have to have those values for the subsequent evaluation of the test statistics.

Reimplemented from RooStats::ToyMCSampler.

Definition at line 112 of file ToyMCSampler.cxx.

◆ GenerateToyData() [5/8]

RooAbsData * RooStats::ToyMCImportanceSampler::GenerateToyData ( RooArgSet paramPoint,
double weight,
std::vector< double > &  impNLLs,
double nullNLL 
) const
virtual

Definition at line 177 of file ToyMCImportanceSampler.cxx.

◆ GenerateToyData() [6/8]

virtual RooAbsData * RooStats::ToyMCSampler::GenerateToyData ( RooArgSet paramPoint,
RooAbsPdf pdf 
) const
inlinevirtual

generates toy data without weight

Reimplemented from RooStats::ToyMCSampler.

Definition at line 104 of file ToyMCSampler.h.

◆ GenerateToyData() [7/8]

RooAbsData * RooStats::ToyMCImportanceSampler::GenerateToyData ( std::vector< double > &  weights) const
virtual

Definition at line 216 of file ToyMCImportanceSampler.cxx.

◆ GenerateToyData() [8/8]

RooAbsData * RooStats::ToyMCImportanceSampler::GenerateToyData ( std::vector< double > &  weights,
std::vector< double > &  nullNLLs,
std::vector< double > &  impNLLs 
) const
virtual

This method generates a toy data set for importance sampling for the given parameter point taking global observables into account.

The values of the generated global observables remain in the pdf's variables. They have to have those values for the subsequent evaluation of the test statistics.

Definition at line 240 of file ToyMCImportanceSampler.cxx.

◆ GetSamplingDistributionsSingleWorker()

RooDataSet * RooStats::ToyMCImportanceSampler::GetSamplingDistributionsSingleWorker ( RooArgSet paramPoint)
overridevirtual

overwrite GetSamplingDistributionsSingleWorker(paramPoint) with a version that loops over nulls and importance densities, but calls the parent ToyMCSampler::GetSamplingDistributionsSingleWorker(paramPoint).

Reimplemented from RooStats::ToyMCSampler.

Definition at line 53 of file ToyMCImportanceSampler.cxx.

◆ IsA()

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

Reimplemented from RooStats::TestStatSampler.

Definition at line 197 of file ToyMCImportanceSampler.h.

◆ SetApplyVeto()

void RooStats::ToyMCImportanceSampler::SetApplyVeto ( bool  b = true)
inline

When set to true, this sets the weight of all toys to zero that do not have the largest likelihood under the density it was generated compared to the other densities.

Definition at line 143 of file ToyMCImportanceSampler.h.

◆ SetConditionalObservables()

virtual void RooStats::ToyMCImportanceSampler::SetConditionalObservables ( const RooArgSet set)
inlinevirtual

set the conditional observables which will be used when creating the NLL so the pdf's will not be normalized on the conditional observables when computing the NLL Since the class use a NLL we need to set the conditional observables if they exist in the model

Definition at line 150 of file ToyMCImportanceSampler.h.

◆ SetDensityToGenerateFromByIndex()

void RooStats::ToyMCImportanceSampler::SetDensityToGenerateFromByIndex ( unsigned int  i,
bool  fromNull = false 
)
inline

specifies the pdf to sample from

Definition at line 61 of file ToyMCImportanceSampler.h.

◆ SetEqualNumToysPerDensity()

void RooStats::ToyMCImportanceSampler::SetEqualNumToysPerDensity ( void  )
inline

Definition at line 167 of file ToyMCImportanceSampler.h.

◆ SetExpIncreasingNumToysPerDensity()

void RooStats::ToyMCImportanceSampler::SetExpIncreasingNumToysPerDensity ( void  )
inline

Definition at line 168 of file ToyMCImportanceSampler.h.

◆ SetParametersForTestStat()

void RooStats::ToyMCImportanceSampler::SetParametersForTestStat ( const RooArgSet nullpoi)
inlineoverridevirtual

overwrite from ToyMCSampler

Implements RooStats::TestStatSampler.

Definition at line 128 of file ToyMCImportanceSampler.h.

◆ SetPdf()

void RooStats::ToyMCImportanceSampler::SetPdf ( RooAbsPdf pdf)
inlineoverridevirtual

overwrite from ToyMCSampler

Implements RooStats::TestStatSampler.

Definition at line 118 of file ToyMCImportanceSampler.h.

◆ SetReuseNLL()

void RooStats::ToyMCImportanceSampler::SetReuseNLL ( bool  r = true)
inline

Definition at line 145 of file ToyMCImportanceSampler.h.

◆ Streamer()

void RooStats::ToyMCImportanceSampler::Streamer ( TBuffer )
overridevirtual

Reimplemented from RooStats::TestStatSampler.

◆ StreamerNVirtual()

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

Definition at line 197 of file ToyMCImportanceSampler.h.

Member Data Documentation

◆ fApplyVeto

bool RooStats::ToyMCImportanceSampler::fApplyVeto
protected

Definition at line 177 of file ToyMCImportanceSampler.h.

◆ fConditionalObs

RooArgSet RooStats::ToyMCImportanceSampler::fConditionalObs
protected

set of conditional observables

Definition at line 179 of file ToyMCImportanceSampler.h.

◆ fGenerateFromNull

bool RooStats::ToyMCImportanceSampler::fGenerateFromNull
protected

Definition at line 176 of file ToyMCImportanceSampler.h.

◆ fImpNLLs

std::vector<RooAbsReal*> RooStats::ToyMCImportanceSampler::fImpNLLs
mutableprotected

!

Definition at line 194 of file ToyMCImportanceSampler.h.

◆ fImportanceDensities

std::vector<RooAbsPdf*> RooStats::ToyMCImportanceSampler::fImportanceDensities
protected

Definition at line 186 of file ToyMCImportanceSampler.h.

◆ fImportanceSnapshots

std::vector<const RooArgSet*> RooStats::ToyMCImportanceSampler::fImportanceSnapshots
protected

Definition at line 187 of file ToyMCImportanceSampler.h.

◆ fIndexGenDensity

unsigned int RooStats::ToyMCImportanceSampler::fIndexGenDensity
protected

Definition at line 175 of file ToyMCImportanceSampler.h.

◆ fNullDensities

std::vector<RooAbsPdf*> RooStats::ToyMCImportanceSampler::fNullDensities
protected

support multiple null densities

Definition at line 182 of file ToyMCImportanceSampler.h.

◆ fNullNLLs

std::vector<RooAbsReal*> RooStats::ToyMCImportanceSampler::fNullNLLs
mutableprotected

!

Definition at line 193 of file ToyMCImportanceSampler.h.

◆ fNullSnapshots

std::vector<const RooArgSet*> RooStats::ToyMCImportanceSampler::fNullSnapshots
mutableprotected

Definition at line 183 of file ToyMCImportanceSampler.h.

◆ fReuseNLL

bool RooStats::ToyMCImportanceSampler::fReuseNLL
protected

Definition at line 189 of file ToyMCImportanceSampler.h.

◆ fToysStrategy

toysStrategies RooStats::ToyMCImportanceSampler::fToysStrategy
protected

Definition at line 191 of file ToyMCImportanceSampler.h.

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