Namespace for the RooStats classes. More...

Namespaces
	HistFactory

	NumberCountingUtils

Classes
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	SamplingSummaryLookup

class	AcceptanceRegion

class	SamplingSummary

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

class	FeldmanCousins
	The FeldmanCousins class (like the Feldman-Cousins technique) is essentially a specific configuration of the more general NeymanConstruction. More...

class	FrequentistCalculator
	Hypothesis Test Calculator using a full frequentist procedure for sampling the test statistic distribution. 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
	This class implements the Hypothesis test calculation using an hybrid (frequentist/bayesian) procedure. 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	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 depratcated 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	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	NumberCountingPdfFactory

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

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	SequentialProposal
	Class implementing a proposal function that samples the parameter space by moving only in one coordinate (choosen randomly) at each step. More...

class	SimpleInterval

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	NuisanceParametersSampler
	Helper class for ToyMCSampler. More...

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	ToyMCPayload

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	PValueToSignificance (Double_t pvalue)

Double_t	SignificanceToPValue (Double_t Z)

void	SetParameters (const RooArgSet desiredVals, RooArgSet paramsToChange)

void	RemoveConstantParameters (RooArgSet *set)

void	RemoveConstantParameters (RooArgList &set)

bool	SetAllConstant (const RooAbsCollection &coll, bool constant=true)

void	RandomizeCollection (RooAbsCollection &set, Bool_t randomizeConstants=kTRUE)

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

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

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

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

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

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

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

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

void	UseNLLOffset (bool on)

bool	IsNLLOffset ()

RooAbsPdf *	StripConstraints (RooAbsPdf &pdf, const RooArgSet &observables)

BranchStore *	CreateBranchStore (const RooDataSet &data)

void	FillTree (TTree &myTree, const RooDataSet &data)

Variables
const ROOT::Math::RootFinder::EType	kRootFinderType = ROOT::Math::RootFinder::kBRENT

bool	gUseOffset = false

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

enum RooStats::toysStrategies

Enumerator
EQUALTOYSPERDENSITY
EXPONENTIALTOYDISTRIBUTION

Definition at line 23 of file ToyMCImportanceSampler.h.

Function Documentation

BranchStore* RooStats::CreateBranchStore ( const RooDataSet & data )

Definition at line 238 of file RooStatsUtils.cxx.

Referenced by FillTree().

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

Definition at line 50 of file RooStatsUtils.cxx.

Referenced by FactorizePdf(), and MakeNuisancePdf().

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

Definition at line 87 of file RooStatsUtils.cxx.

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

Definition at line 263 of file RooStatsUtils.cxx.

Referenced by GetAsTTree().

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

Definition at line 291 of file RooStatsUtils.cxx.

Referenced by rs101_limitexample().

bool RooStats::IsNLLOffset ( )

Definition at line 46 of file RooStatsUtils.cxx.

Referenced by RooStats::LikelihoodInterval::CreateMinimizer(), RooStats::ProfileLikelihoodCalculator::DoGlobalFit(), RooStats::AsymptoticCalculator::EvaluateNLL(), RooStats::ProfileLikelihoodCalculator::GetHypoTest(), RooStats::AsymptoticCalculator::MakeAsimovData(), RooStats::FrequentistCalculator::PreAltHook(), RooStats::FrequentistCalculator::PreNullHook(), and RooStats::ProfileLikelihoodTestStat::ProfileLikelihoodTestStat().

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

Definition at line 98 of file RooStatsUtils.cxx.

Referenced by RooStats::AsymptoticCalculator::MakeAsimovData(), MakeNuisancePdf(), RooStats::HybridCalculator::SetAlternateModel(), RooStats::HybridCalculator::SetNullModel(), StandardBayesianNumericalDemo(), and StandardHypoTestDemo().

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

Definition at line 111 of file RooStatsUtils.cxx.

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

Definition at line 181 of file RooStatsUtils.cxx.

Referenced by RooStats::SimpleLikelihoodRatioTestStat::Evaluate(), and MakeUnconstrainedPdf().

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

Definition at line 192 of file RooStatsUtils.cxx.

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

Definition at line 299 of file RooStatsUtils.cxx.

Referenced by RooStats::ProfileLikelihoodTestStat::EvaluateProfileLikelihood(), and RooStats::HypoTestInverter::RebuildDistributions().

Double_t RooStats::PValueToSignificance ( Double_t pvalue )

inline

Definition at line 59 of file RooStatsUtils.h.

Referenced by RooStats::NumberCountingUtils::BinomialExpZ(), RooStats::NumberCountingUtils::BinomialObsZ(), RooStats::NumberCountingUtils::BinomialWithTauExpZ(), RooStats::NumberCountingUtils::BinomialWithTauObsZ(), ClassImp(), RooStats::HypoTestResult::Significance(), and Zbi_Zgamma().

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

inline

Definition at line 110 of file RooStatsUtils.h.

Referenced by RooStats::MetropolisHastings::ConstructChain(), and RooStats::UniformProposal::Propose().

void RooStats::RemoveConstantParameters ( RooArgSet * set )

inline

Definition at line 73 of file RooStatsUtils.h.

Referenced by RooStats::BayesianCalculator::BayesianCalculator(), RooStats::LikelihoodInterval::CreateMinimizer(), RooStats::ProfileLikelihoodCalculator::DoGlobalFit(), RooStats::MaxLikelihoodEstimateTestStat::Evaluate(), RooStats::AsymptoticCalculator::EvaluateNLL(), RooStats::ProfileLikelihoodTestStat::EvaluateProfileLikelihood(), RooStats::LikelihoodInterval::FindLimits(), RooStats::LikelihoodInterval::GetContourPoints(), RooStats::ProfileLikelihoodCalculator::GetHypoTest(), RooStats::ProfileLikelihoodCalculator::GetInterval(), RooStats::MCMCCalculator::GetInterval(), RooStats::BayesianCalculator::GetPosteriorFunction(), RooStats::ModelConfig::GuessObsAndNuisance(), RooStats::AsymptoticCalculator::Initialize(), RooStats::AsymptoticCalculator::MakeAsimovData(), RooStats::FrequentistCalculator::PreAltHook(), RooStats::FrequentistCalculator::PreNullHook(), RooStats::MetropolisHastings::SetChainParameters(), RooStats::BayesianCalculator::SetModel(), and RooStats::MetropolisHastings::SetParameters().

void RooStats::RemoveConstantParameters ( RooArgList & set )

inline

Definition at line 83 of file RooStatsUtils.h.

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

inline

Definition at line 93 of file RooStatsUtils.h.

Referenced by RooStats::AsymptoticCalculator::EvaluateNLL(), RooStats::AsymptoticCalculator::MakeAsimovData(), and StandardHypoTestDemo().

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

inline

Definition at line 69 of file RooStatsUtils.h.

Referenced by RooStats::MarkovChain::Add(), RooStats::MarkovChain::AddFast(), RooStats::SPlot::AddSWeight(), ClassImp(), RooStats::MetropolisHastings::ConstructChain(), RooStats::PdfProposal::GetProposalDensity(), RooStats::LikelihoodInterval::IsInInterval(), and RooStats::PdfProposal::Propose().

Double_t RooStats::SignificanceToPValue ( Double_t Z )

inline

Definition at line 64 of file RooStatsUtils.h.

Referenced by OneSidedFrequentistUpperLimitWithBands(), and TwoSidedFrequentistUpperLimitWithBands().

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

Definition at line 120 of file RooStatsUtils.cxx.

Referenced by MakeUnconstrainedPdf().

void RooStats::UseNLLOffset ( bool on )

Definition at line 41 of file RooStatsUtils.cxx.

Referenced by StandardHypoTestInvDemo().

Variable Documentation

bool RooStats::gUseOffset = false

Definition at line 39 of file RooStatsUtils.cxx.

Referenced by IsNLLOffset(), and UseNLLOffset().

const ROOT::Math::RootFinder::EType RooStats::kRootFinderType = ROOT::Math::RootFinder::kBRENT

Definition at line 68 of file BayesianCalculator.cxx.

Namespaces

Classes

Enumerations

Functions

Variables

Detailed Description

Enumeration Type Documentation

Function Documentation

Variable Documentation