11 #ifndef ROOSTATS_AsymptoticCalculator 12 #define ROOSTATS_AsymptoticCalculator 34 bool nominalAsimov =
false 64 static double GetExpectedPValues(
double pnull,
double palt,
double nsigma,
bool usecls,
bool oneSided =
true );
123 &binVolume,
int &ibin);
static RooAbsData * GenerateAsimovData(const RooAbsPdf &pdf, const RooArgSet &observables)
generate the asimov data for the observables (not the global ones) need to deal with the case of a si...
virtual void SetNullModel(const ModelConfig &nullModel)
re-implementation of setters since they are needed to re-initialize the calculator ...
ModelConfig is a simple class that holds configuration information specifying how a model should be u...
static double EvaluateNLL(RooAbsPdf &pdf, RooAbsData &data, const RooArgSet *condObs, const RooArgSet *globObs, const RooArgSet *poiSet=0)
static double GetExpectedPValues(double pnull, double palt, double nsigma, bool usecls, bool oneSided=true)
function given the null and the alt p value - return the expected one given the N - sigma value ...
bool IsOneSidedDiscovery() const
RooProdPdf is an efficient implementation of a product of PDFs of the form.
HypoTestResult is a base class for results from hypothesis tests.
const RooArgSet & GetBestFitParams() const
return best fit value for all parameters
AsymptoticCalculator(RooAbsData &data, const ModelConfig &altModel, const ModelConfig &nullModel, bool nominalAsimov=false)
constructor for asymptotic calculator from Data set and ModelConfig
static void SetPrintLevel(int level)
set print level (static function)
static RooAbsData * GenerateCountingAsimovData(RooAbsPdf &pdf, const RooArgSet &obs, const RooRealVar &weightVar, RooCategory *channelCat=0)
generate counting Asimov data for the case when the pdf cannot be extended assume pdf is a RooPoisson...
Common base class for the Hypothesis Test Calculators.
static RooAbsData * MakeAsimovData(RooAbsData &data, const ModelConfig &model, const RooArgSet &poiValues, RooArgSet &globObs, const RooArgSet *genPoiValues=0)
make the asimov data from the ModelConfig and list of poi - return data set and snapshot of global ob...
static void FillBins(const RooAbsPdf &pdf, const RooArgList &obs, RooAbsData &data, int &index, double &binVolume, int &ibin)
fill bins by looping recursively on observables
#define ClassDef(name, id)
const RooArgSet & GetBestFitPoi() const
return snapshot of the best fit parameter
void SetQTilde(bool on)
set using of qtilde, by default is controlled if RoORealVar is limited or not
virtual HypoTestResult * GetHypoTest() const
re-implement HypoTest computation using the asymptotic
virtual void SetData(RooAbsData &data)
RooRealVar represents a fundamental (non-derived) real valued object.
bool Initialize() const
initialize the calculator by performing a global fit and make the Asimov data set ...
void SetTwoSided()
set the test statistics for two sided (in case of upper limits for discovery does not make really sen...
RooAbsArg * first() const
static bool SetObsToExpected(RooAbsPdf &pdf, const RooArgSet &obs)
set observed value to the expected one works for Gaussian, Poisson or LogNormal assumes mean paramete...
RooAbsData is the common abstract base class for binned and unbinned datasets.
RooCategory represents a fundamental (non-derived) discrete value object.
virtual void SetAlternateModel(const ModelConfig &altModel)
Namespace for the RooStats classes.
int fUseQTilde
flag to check if calculator is initialized
void SetOneSidedDiscovery(bool on)
set the test statistics for one-sided discovery
void SetOneSided(bool on)
set test statistic for one sided (upper limits)
RooAbsPdf is the abstract interface for all probability density functions The class provides hybrid a...
virtual void SetData(RooAbsData &data)
virtual void SetAlternateModel(const ModelConfig &altModel)
virtual void SetNullModel(const ModelConfig &nullModel)
Hypothesis Test Calculator based on the asymptotic formulae for the profile likelihood ratio...
const RooRealVar * GetMuHat() const
return best fit parameter (firs of poi)
static RooAbsData * GenerateAsimovDataSinglePdf(const RooAbsPdf &pdf, const RooArgSet &obs, const RooRealVar &weightVar, RooCategory *channelCat=0)
compute the asimov data set for an observable of a pdf use the number of bins sets in the observables...