12#ifndef ROOSTATS_MCMCCalculator
13#define ROOSTATS_MCMCCalculator
134 coutE(InputArguments) <<
"MCMCInterval::SetEpsilon will not allow "
135 <<
"negative epsilon value" << std::endl;
157 coutE(InputArguments) <<
"MCMCInterval::SetDelta will not allow "
158 <<
"negative delta value" << std::endl;
196 for (
auto *
r : dynamic_range_cast<RooRealVar *>(coll)){
size_t size(const MatrixT &matrix)
retrieve the size of a square matrix
#define ClassDefOverride(name, id)
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void data
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t r
Abstract container object that can hold multiple RooAbsArg objects.
virtual void removeAll()
Remove all arguments from our set, deleting them if we own them.
virtual bool add(const RooAbsArg &var, bool silent=false)
Add the specified argument to list.
Abstract base class for binned and unbinned datasets.
Abstract interface for all probability density functions.
RooArgList is a container object that can hold multiple RooAbsArg objects.
RooArgSet is a container object that can hold multiple RooAbsArg objects.
IntervalCalculator is an interface class for a tools which produce RooStats ConfIntervals.
Bayesian Calculator estimating an interval or a credible region using the Markov-Chain Monte Carlo me...
virtual void SetPriorPdf(RooAbsPdf &pdf)
Set the Prior Pdf if not already there.
RooArgSet fChainParams
parameters to store in the chain (if not specified they are all of them )
virtual void SetNumBurnInSteps(Int_t numBurnInSteps)
set the number of steps in the chain to discard as burn-in, starting from the first
enum MCMCInterval::IntervalType fIntervalType
virtual void SetUseSparseHist(bool useSparseHist)
set whether to use sparse histogram (if using histogram at all)
RooAbsPdf * fPdf
pointer to common PDF (owned by the workspace)
RooAbsData * fData
pointer to the data (owned by the workspace)
bool fUseKeys
whether to use kernel estimation to determine interval
virtual void SetNumBins(Int_t numBins)
set the number of bins to create for each axis when constructing the interval
bool fUseSparseHist
whether to use sparse histogram (if using hist at all)
void SetBins(const RooAbsCollection &coll, Int_t numBins) const
void SetupBasicUsage()
Constructor for automatic configuration with basic settings.
double fDelta
acceptable error for Keys cutoffs being equal
MCMCCalculator()
default constructor
void SetModel(const ModelConfig &model) override
Set the Model.
virtual void SetLeftSideTailFraction(double a)
Set the left side tail fraction.
virtual void SetKeysConfidenceAccuracy(double epsilon)
Set the desired level of confidence-level accuracy for Keys interval determination.
virtual void SetNumIters(Int_t numIters)
set the number of iterations to run the metropolis algorithm
virtual void SetNuisanceParameters(const RooArgSet &set)
specify the nuisance parameters (eg. the rest of the parameters)
RooArgSet fNuisParams
nuisance parameters for interval (not really used)
void SetConfidenceLevel(double cl) override
set the confidence level for the interval (eg. 0.95 for a 95% Confidence Interval)
virtual void SetParameters(const RooArgSet &set)
specify the parameters of interest in the interval
double Size() const override
Get the size of the test (eg. rate of Type I error)
void SetData(RooAbsData &data) override
Set the DataSet if not already there.
Int_t fNumIters
number of iterations to run metropolis algorithm
virtual void SetKeysTerminationThreshold(double delta)
When the shortest interval using Keys PDF could not be found to have the desired confidence level +/-...
Int_t fNumBins
set the number of bins to create for each axis when constructing the interval
RooArgSet fConditionalObs
conditional observables
double fEpsilon
acceptable error for Keys interval determination
void SetTestSize(double size) override
set the size of the test (rate of Type I error) ( Eg. 0.05 for a 95% Confidence Interval)
double fLeftSideTF
left side tail-fraction for interval
virtual void SetAxes(RooArgList &axes)
set which variables to put on each axis
double fSize
size of the test (eg. specified rate of Type I error)
Int_t fNumBurnInSteps
number of iterations to discard as burn-in, starting from the first
RooArgSet fPOI
parameters of interest for interval
virtual void SetPdf(RooAbsPdf &pdf)
Set the Pdf if not already there.
RooArgList * fAxes
which variables to put on each axis
RooArgSet fGlobalObs
global observables
MCMCInterval * GetInterval() const override
Main interface to get a ConfInterval.
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 nor...
virtual void SetProposalFunction(ProposalFunction &proposalFunction)
set the proposal function for suggesting new points for the MCMC
virtual void SetGlobalObservables(const RooArgSet &set)
set the global observables which will be used when creating the NLL so the constraint pdf's will be n...
virtual void SetIntervalType(enum MCMCInterval::IntervalType intervalType)
set what type of interval to have the MCMCInterval represent
RooAbsPdf * fPriorPdf
pointer to prior PDF (owned by the workspace)
ProposalFunction * fPropFunc
Proposal function for MCMC integration.
virtual void SetUseKeys(bool useKeys)
set whether to use kernel estimation to determine the interval
double ConfidenceLevel() const override
Get the Confidence level for the test.
virtual void SetChainParameters(const RooArgSet &set)
specify the parameters to store in the Markov chain By default all the parameters are stored
MCMCInterval is a concrete implementation of the RooStats::ConfInterval interface.
ModelConfig is a simple class that holds configuration information specifying how a model should be u...
ProposalFunction is an interface for all proposal functions that would be used with a Markov Chain Mo...
The TNamed class is the base class for all named ROOT classes.
RooStats::ModelConfig ModelConfig
Namespace for the RooStats classes.