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Reference Guide
Namespaces | Classes | Enumerations | Functions | Variables
RooStats Namespace Reference

Namespace for the RooStats classes. More...

Namespaces

 HistFactory
 
 NumberCountingUtils
 

Classes

class  AcceptanceRegion
 
class  AsymptoticCalculator
 Hypothesis Test Calculator based on the asymptotic formulae for the profile likelihood ratio. More...
 
class  BayesianCalculator
 BayesianCalculator is a concrete implementation of IntervalCalculator, providing the computation of a credible interval using a Bayesian method. More...
 
class  BernsteinCorrection
 BernsteinCorrection is a utility in RooStats to augment a nominal PDF with a polynomial correction term. More...
 
class  CombinedCalculator
 CombinedCalculator is an interface class for a tools which can produce both RooStats HypoTestResults and ConfIntervals. More...
 
class  ConfidenceBelt
 ConfidenceBelt is a concrete implementation of the ConfInterval interface. More...
 
class  ConfInterval
 ConfInterval is an interface class for a generic interval in the RooStats framework. More...
 
class  DebuggingSampler
 
class  DebuggingTestStat
 
class  DetailedOutputAggregator
 This class is designed to aid in the construction of RooDataSets and RooArgSets, particularly those naturally arising in fitting operations. More...
 
class  FeldmanCousins
 The FeldmanCousins class (like the Feldman-Cousins technique) is essentially a specific configuration of the more general NeymanConstruction. More...
 
class  FrequentistCalculator
 Does a frequentist hypothesis test. More...
 
class  Heaviside
 Represents the Heaviside function. More...
 
class  HLFactory
 HLFactory is an High Level model Factory allows you to describe your models in a configuration file (datacards) acting as an interface with the RooFactoryWSTool. More...
 
class  HybridCalculator
 Same purpose as HybridCalculatorOriginal, but different implementation. More...
 
class  HybridCalculatorOriginal
 HybridCalculatorOriginal class. More...
 
class  HybridPlot
 This class provides the plots for the result of a study performed with the HybridCalculatorOriginal class. More...
 
class  HybridResult
 Class encapsulating the result of the HybridCalculatorOriginal. More...
 
class  HypoTestCalculator
 HypoTestCalculator is an interface class for a tools which produce RooStats HypoTestResults. More...
 
class  HypoTestCalculatorGeneric
 Common base class for the Hypothesis Test Calculators. More...
 
class  HypoTestInverter
 HypoTestInverter class for performing an hypothesis test inversion by scanning the hypothesis test results of an HypoTestCalculator for various values of the parameter of interest. More...
 
class  HypoTestInverterOriginal
 This class is now deprecated and to be replaced by the HypoTestInverter. More...
 
class  HypoTestInverterPlot
 Class to plot an HypoTestInverterResult, result of the HypoTestInverter calculator. More...
 
class  HypoTestInverterResult
 HypoTestInverterResult class holds the array of hypothesis test results and compute a confidence interval. More...
 
class  HypoTestPlot
 This class provides the plots for the result of a study performed with any of the HypoTestCalculatorGeneric (e.g. More...
 
class  HypoTestResult
 HypoTestResult is a base class for results from hypothesis tests. More...
 
class  IntervalCalculator
 IntervalCalculator is an interface class for a tools which produce RooStats ConfIntervals. More...
 
class  LikelihoodInterval
 LikelihoodInterval is a concrete implementation of the RooStats::ConfInterval interface. More...
 
class  LikelihoodIntervalPlot
 This class provides simple and straightforward utilities to plot a LikelihoodInterval object. More...
 
class  MarkovChain
 Stores the steps in a Markov Chain of points. More...
 
class  MaxLikelihoodEstimateTestStat
 MaxLikelihoodEstimateTestStat: TestStatistic that returns maximum likelihood estimate of a specified parameter. More...
 
class  MCMCCalculator
 Bayesian Calculator estimating an interval or a credible region using the Markov-Chain Monte Carlo method to integrate the likelihood function with the prior to obtain the posterior function. More...
 
class  MCMCInterval
 MCMCInterval is a concrete implementation of the RooStats::ConfInterval interface. More...
 
class  MCMCIntervalPlot
 This class provides simple and straightforward utilities to plot a MCMCInterval object. More...
 
class  MetropolisHastings
 This class uses the Metropolis-Hastings algorithm to construct a Markov Chain of data points using Monte Carlo. More...
 
class  MinNLLTestStat
 MinNLLTestStat is an implementation of the TestStatistic interface that calculates the minimum value of the negative log likelihood function and returns it as a test statistic. More...
 
class  ModelConfig
 ModelConfig is a simple class that holds configuration information specifying how a model should be used in the context of various RooStats tools. More...
 
class  NeymanConstruction
 NeymanConstruction is a concrete implementation of the NeymanConstruction interface that, as the name suggests, performs a NeymanConstruction. More...
 
class  NuisanceParametersSampler
 Helper class for ToyMCSampler. More...
 
class  NumberCountingPdfFactory
 A factory for building PDFs and data for a number counting combination. More...
 
class  NumEventsTestStat
 NumEventsTestStat is a simple implementation of the TestStatistic interface used for simple number counting. More...
 
class  PdfProposal
 PdfProposal is a concrete implementation of the ProposalFunction interface. More...
 
class  PointSetInterval
 PointSetInterval is a concrete implementation of the ConfInterval interface. More...
 
class  ProfileInspector
 Utility class to plot conditional MLE of nuisance parameters vs. More...
 
class  ProfileLikelihoodCalculator
 ProfileLikelihoodCalculator is a concrete implementation of CombinedCalculator (the interface class for a tools which can produce both RooStats HypoTestResults and ConfIntervals). More...
 
class  ProfileLikelihoodTestStat
 ProfileLikelihoodTestStat is an implementation of the TestStatistic interface that calculates the profile likelihood ratio at a particular parameter point given a dataset. More...
 
class  ProofConfig
 Holds configuration options for proof and proof-lite. More...
 
class  ProposalFunction
 ProposalFunction is an interface for all proposal functions that would be used with a Markov Chain Monte Carlo algorithm. More...
 
class  ProposalHelper
 
class  RatioOfProfiledLikelihoodsTestStat
 TestStatistic that returns the ratio of profiled likelihoods. More...
 
class  SamplingDistPlot
 This class provides simple and straightforward utilities to plot SamplingDistribution objects. More...
 
class  SamplingDistribution
 This class simply holds a sampling distribution of some test statistic. More...
 
class  SamplingSummary
 
class  SamplingSummaryLookup
 
class  SequentialProposal
 Class implementing a proposal function that samples the parameter space by moving only in one coordinate (chosen randomly) at each step. More...
 
class  SimpleInterval
 SimpleInterval is a concrete implementation of the ConfInterval interface. More...
 
class  SimpleLikelihoodRatioTestStat
 TestStatistic class that returns -log(L[null] / L[alt]) where L is the likelihood. More...
 
class  SPlot
 This class calculates sWeights used to create an sPlot. More...
 
class  TestStatistic
 TestStatistic is an interface class to provide a facility for construction test statistics distributions to the NeymanConstruction class. More...
 
class  TestStatSampler
 TestStatSampler is an interface class for a tools which produce RooStats SamplingDistributions. More...
 
class  ToyMCImportanceSampler
 ToyMCImportanceSampler is an extension of the ToyMCSampler for Importance Sampling. More...
 
class  ToyMCPayload
 
class  ToyMCSampler
 ToyMCSampler is an implementation of the TestStatSampler interface. More...
 
class  ToyMCStudy
 ToyMCStudy is an implementation of RooAbsStudy for toy Monte Carlo sampling. More...
 
class  UniformProposal
 UniformProposal is a concrete implementation of the ProposalFunction interface for use with a Markov Chain Monte Carlo algorithm. More...
 
class  UpperLimitMCSModule
 This class allow to compute in the ToyMcStudy framework the ProfileLikelihood upper limit for each toy-MC sample generated. More...
 

Enumerations

enum  toysStrategies { EQUALTOYSPERDENSITY, EXPONENTIALTOYDISTRIBUTION }
 

Functions

Double_t AsimovSignificance (Double_t s, Double_t b, Double_t sigma_b=0.0)
 Compute the Asimov Median significance for a Poisson process with s = expected number of signal events, b = expected numner of background events and optionally sigma_b = expected uncertainty of backgorund events. More...
 
BranchStore * CreateBranchStore (const RooDataSet &data)
 
void FactorizePdf (const RooArgSet &observables, RooAbsPdf &pdf, RooArgList &obsTerms, RooArgList &constraints)
 
void FactorizePdf (RooStats::ModelConfig &model, RooAbsPdf &pdf, RooArgList &obsTerms, RooArgList &constraints)
 
void FillTree (TTree &myTree, const RooDataSet &data)
 
TTreeGetAsTTree (TString name, TString desc, const RooDataSet &data)
 
bool IsNLLOffset ()
 
RooAbsPdfMakeNuisancePdf (RooAbsPdf &pdf, const RooArgSet &observables, const char *name)
 
RooAbsPdfMakeNuisancePdf (const RooStats::ModelConfig &model, const char *name)
 
RooAbsPdfMakeUnconstrainedPdf (RooAbsPdf &pdf, const RooArgSet &observables, const char *name=NULL)
 
RooAbsPdfMakeUnconstrainedPdf (const RooStats::ModelConfig &model, const char *name=NULL)
 
void PrintListContent (const RooArgList &l, std::ostream &os=std::cout)
 
Double_t PValueToSignificance (Double_t pvalue)
 returns one-sided significance corresponding to a p-value More...
 
void RandomizeCollection (RooAbsCollection &set, Bool_t randomizeConstants=kTRUE)
 
void RemoveConstantParameters (RooArgSet *set)
 
void RemoveConstantParameters (RooArgList &set)
 
bool SetAllConstant (const RooAbsCollection &coll, bool constant=true)
 
void SetParameters (const RooArgSet *desiredVals, RooArgSet *paramsToChange)
 
Double_t SignificanceToPValue (Double_t Z)
 returns p-value corresponding to a 1-sided significance More...
 
RooAbsPdfStripConstraints (RooAbsPdf &pdf, const RooArgSet &observables)
 
void UseNLLOffset (bool on)
 

Variables

bool gUseOffset = false
 
const ROOT::Math::RootFinder::EType kRootFinderType = ROOT::Math::RootFinder::kBRENT
 

Detailed Description

Namespace for the RooStats classes.

All the classes of the RooStats package are in the RooStats namespace. In addition the namespace contain a set of utility functions.

Enumeration Type Documentation

◆ toysStrategies

Enumerator
EQUALTOYSPERDENSITY 
EXPONENTIALTOYDISTRIBUTION 

Definition at line 19 of file ToyMCImportanceSampler.h.

Function Documentation

◆ AsimovSignificance()

Double_t RooStats::AsimovSignificance ( Double_t  s,
Double_t  b,
Double_t  sigma_b = 0.0 
)

Compute the Asimov Median significance for a Poisson process with s = expected number of signal events, b = expected numner of background events and optionally sigma_b = expected uncertainty of backgorund events.

Definition at line 36 of file RooStatsUtils.cxx.

◆ CreateBranchStore()

BranchStore* RooStats::CreateBranchStore ( const RooDataSet data)

Definition at line 256 of file RooStatsUtils.cxx.

◆ FactorizePdf() [1/2]

void RooStats::FactorizePdf ( const RooArgSet observables,
RooAbsPdf pdf,
RooArgList obsTerms,
RooArgList constraints 
)

Definition at line 68 of file RooStatsUtils.cxx.

◆ FactorizePdf() [2/2]

void RooStats::FactorizePdf ( RooStats::ModelConfig model,
RooAbsPdf pdf,
RooArgList obsTerms,
RooArgList constraints 
)

Definition at line 105 of file RooStatsUtils.cxx.

◆ FillTree()

void RooStats::FillTree ( TTree myTree,
const RooDataSet data 
)

Definition at line 281 of file RooStatsUtils.cxx.

◆ GetAsTTree()

TTree * RooStats::GetAsTTree ( TString  name,
TString  desc,
const RooDataSet data 
)

Definition at line 309 of file RooStatsUtils.cxx.

◆ IsNLLOffset()

bool RooStats::IsNLLOffset ( )

Definition at line 64 of file RooStatsUtils.cxx.

◆ MakeNuisancePdf() [1/2]

RooAbsPdf * RooStats::MakeNuisancePdf ( RooAbsPdf pdf,
const RooArgSet observables,
const char *  name 
)

Definition at line 116 of file RooStatsUtils.cxx.

◆ MakeNuisancePdf() [2/2]

RooAbsPdf * RooStats::MakeNuisancePdf ( const RooStats::ModelConfig model,
const char *  name 
)

Definition at line 129 of file RooStatsUtils.cxx.

◆ MakeUnconstrainedPdf() [1/2]

RooAbsPdf * RooStats::MakeUnconstrainedPdf ( RooAbsPdf pdf,
const RooArgSet observables,
const char *  name = NULL 
)

Definition at line 199 of file RooStatsUtils.cxx.

◆ MakeUnconstrainedPdf() [2/2]

RooAbsPdf * RooStats::MakeUnconstrainedPdf ( const RooStats::ModelConfig model,
const char *  name = NULL 
)

Definition at line 210 of file RooStatsUtils.cxx.

◆ PrintListContent()

void RooStats::PrintListContent ( const RooArgList l,
std::ostream &  os = std::cout 
)

Definition at line 317 of file RooStatsUtils.cxx.

◆ PValueToSignificance()

Double_t RooStats::PValueToSignificance ( Double_t  pvalue)
inline

returns one-sided significance corresponding to a p-value

Definition at line 44 of file RooStatsUtils.h.

◆ RandomizeCollection()

void RooStats::RandomizeCollection ( RooAbsCollection set,
Bool_t  randomizeConstants = kTRUE 
)
inline

Definition at line 99 of file RooStatsUtils.h.

◆ RemoveConstantParameters() [1/2]

void RooStats::RemoveConstantParameters ( RooArgSet set)
inline

Definition at line 62 of file RooStatsUtils.h.

◆ RemoveConstantParameters() [2/2]

void RooStats::RemoveConstantParameters ( RooArgList set)
inline

Definition at line 72 of file RooStatsUtils.h.

◆ SetAllConstant()

bool RooStats::SetAllConstant ( const RooAbsCollection coll,
bool  constant = true 
)
inline

Definition at line 82 of file RooStatsUtils.h.

◆ SetParameters()

void RooStats::SetParameters ( const RooArgSet desiredVals,
RooArgSet paramsToChange 
)
inline

Definition at line 58 of file RooStatsUtils.h.

◆ SignificanceToPValue()

Double_t RooStats::SignificanceToPValue ( Double_t  Z)
inline

returns p-value corresponding to a 1-sided significance

Definition at line 49 of file RooStatsUtils.h.

◆ StripConstraints()

RooAbsPdf* RooStats::StripConstraints ( RooAbsPdf pdf,
const RooArgSet observables 
)

Definition at line 138 of file RooStatsUtils.cxx.

◆ UseNLLOffset()

void RooStats::UseNLLOffset ( bool  on)

Definition at line 59 of file RooStatsUtils.cxx.

Variable Documentation

◆ gUseOffset

bool RooStats::gUseOffset = false

Definition at line 34 of file RooStatsUtils.cxx.

◆ kRootFinderType

Definition at line 103 of file BayesianCalculator.cxx.