BayesianCalculator is a concrete implementation of IntervalCalculator, providing the computation of a credible interval using a Bayesian method.
The class works only for one single parameter of interest and it integrates the likelihood function with the given prior probability density function to compute the posterior probability. The result of the class is a one dimensional interval (class SimpleInterval ), which is obtained from inverting the cumulative posterior distribution. This calculator works then only for model with a single parameter of interest. The model can instead have several nuisance parameters which are integrated (marginalized) in the computation of the posterior function. The integration and normalization of the posterior is computed using numerical integration methods provided by ROOT. See the MCMCCalculator for model with multiple parameters of interest.
The interface allows one to construct the class by passing the data set, probability density function for the model, the prior functions and then the parameter of interest to scan. The nuisance parameters can also be passed to be marginalized when computing the posterior. Alternatively, the class can be constructed by passing the data and the ModelConfig containing all the needed information (model pdf, prior pdf, parameter of interest, nuisance parameters, etc..)
After configuring the calculator, one only needs to ask GetInterval(), which will return an SimpleInterval object. By default the extreme of the integral are obtained by inverting directly the cumulative posterior distribution. By using the method SetScanOfPosterior(nbins) the interval is then obtained by scanning the posterior function in the given number of points. The first method is in general faster but it requires an integration one extra dimension ( in the poi in addition to the nuisance parameters), therefore in some case it can be less robust.
The class can also return the posterior function (method GetPosteriorFunction) or if needed the normalized posterior function (the posterior pdf) (method GetPosteriorPdf). A posterior plot is also obtained using the GetPosteriorPlot method.
The class allows to use different integration methods for integrating in (marginalizing) the nuisances and in the poi. All the numerical integration methods of ROOT can be used via the method SetIntegrationType (see more in the documentation of this method).
Calculator estimating a credible interval using the Bayesian procedure. The calculator computes given the model the posterior distribution and estimates the credible interval from the given function.
Definition at line 37 of file BayesianCalculator.h.
Public Member Functions | |
BayesianCalculator () | |
constructor | |
BayesianCalculator (RooAbsData &data, ModelConfig &model) | |
Constructor from a data set and a ModelConfig model pdf, poi and nuisances will be taken from the ModelConfig. | |
BayesianCalculator (RooAbsData &data, RooAbsPdf &pdf, const RooArgSet &POI, RooAbsPdf &priorPdf, const RooArgSet *nuisanceParameters=nullptr) | |
Constructor from data set, model pdf, parameter of interests and prior pdf If nuisance parameters are given they will be integrated according either to the prior or their constraint term included in the model. | |
~BayesianCalculator () override | |
destructor | |
double | ConfidenceLevel () const override |
Get the Confidence level for the test. | |
void | ForceNuisancePdf (RooAbsPdf &pdf) |
SimpleInterval * | GetInterval () const override |
compute the interval. | |
double | GetMode () const |
return the mode (most probable value of the posterior function) | |
RooAbsReal * | GetPosteriorFunction () const |
return posterior function (object is managed by the BayesianCalculator class) | |
TH1 * | GetPosteriorHistogram () const |
return the approximate posterior as histogram (TH1 object). Note the object is managed by the BayesianCalculator class | |
RooAbsPdf * | GetPosteriorPdf () const |
return posterior pdf (object is managed by the user) | |
RooPlot * | GetPosteriorPlot (bool norm=false, double precision=0.01) const |
get the plot with option to get it normalized | |
TClass * | IsA () const override |
void | SetBrfPrecision (double precision) |
set the precision of the Root Finder | |
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 | |
void | SetConfidenceLevel (double cl) override |
set the confidence level for the interval (eg. 0.95 for a 95% Confidence Interval) | |
void | SetData (RooAbsData &data) override |
Set the DataSet ( add to the workspace if not already there ?) | |
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 normalized correctly on the global observables when computing the NLL | |
void | SetIntegrationType (const char *type) |
set the integration type (possible type are) : | |
void | SetLeftSideTailFraction (double leftSideFraction) |
set the fraction of probability content on the left tail Central limits use 0.5 (default case) for upper limits it is 0 and 1 for lower limit For shortest intervals a negative value (i.e. | |
void | SetModel (const ModelConfig &model) override |
set the model via the ModelConfig | |
virtual void | SetNuisanceParameters (const RooArgSet &set) |
specify the nuisance parameters (eg. the rest of the parameters) | |
virtual void | SetNumIters (Int_t numIters) |
set the number of iterations when running a MC integration algorithm If not set use default algorithmic values In case of ToyMC sampling of the nuisance the value is 100 In case of using the GSL MCintegrations types the default value is defined in ROOT::Math::IntegratorMultiDimOptions::DefaultNCalls() | |
virtual void | SetParameters (const RooArgSet &set) |
specify the parameters of interest in the interval | |
virtual void | SetPriorPdf (RooAbsPdf &pdf) |
Set only the Prior Pdf. | |
void | SetScanOfPosterior (int nbin=100) |
use directly the approximate posterior function obtained by binning it in nbins by default the cdf is used by integrating the posterior if a value of nbin <= 0 the cdf function will be used | |
void | SetShortestInterval () |
set the Bayesian calculator to compute the shortest interval (default is central interval) to switch off SetLeftSideTailFraction to the right value | |
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 | Size () const override |
Get the size of the test (eg. rate of Type I error) | |
void | Streamer (TBuffer &) override |
void | StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b) |
Public Member Functions inherited from RooStats::IntervalCalculator | |
virtual | ~IntervalCalculator () |
void | StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b) |
Public Member Functions inherited from TNamed | |
TNamed () | |
TNamed (const char *name, const char *title) | |
TNamed (const TNamed &named) | |
TNamed copy ctor. | |
TNamed (const TString &name, const TString &title) | |
virtual | ~TNamed () |
TNamed destructor. | |
void | Clear (Option_t *option="") override |
Set name and title to empty strings (""). | |
TObject * | Clone (const char *newname="") const override |
Make a clone of an object using the Streamer facility. | |
Int_t | Compare (const TObject *obj) const override |
Compare two TNamed objects. | |
void | Copy (TObject &named) const override |
Copy this to obj. | |
virtual void | FillBuffer (char *&buffer) |
Encode TNamed into output buffer. | |
const char * | GetName () const override |
Returns name of object. | |
const char * | GetTitle () const override |
Returns title of object. | |
ULong_t | Hash () const override |
Return hash value for this object. | |
TClass * | IsA () const override |
Bool_t | IsSortable () const override |
void | ls (Option_t *option="") const override |
List TNamed name and title. | |
TNamed & | operator= (const TNamed &rhs) |
TNamed assignment operator. | |
void | Print (Option_t *option="") const override |
Print TNamed name and title. | |
virtual void | SetName (const char *name) |
Set the name of the TNamed. | |
virtual void | SetNameTitle (const char *name, const char *title) |
Set all the TNamed parameters (name and title). | |
virtual void | SetTitle (const char *title="") |
Set the title of the TNamed. | |
virtual Int_t | Sizeof () const |
Return size of the TNamed part of the TObject. | |
void | Streamer (TBuffer &) override |
Stream an object of class TObject. | |
void | StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b) |
Public Member Functions inherited from TObject | |
TObject () | |
TObject constructor. | |
TObject (const TObject &object) | |
TObject copy ctor. | |
virtual | ~TObject () |
TObject destructor. | |
void | AbstractMethod (const char *method) const |
Use this method to implement an "abstract" method that you don't want to leave purely abstract. | |
virtual void | AppendPad (Option_t *option="") |
Append graphics object to current pad. | |
virtual void | Browse (TBrowser *b) |
Browse object. May be overridden for another default action. | |
ULong_t | CheckedHash () |
Check and record whether this class has a consistent Hash/RecursiveRemove setup (*) and then return the regular Hash value for this object. | |
virtual const char * | ClassName () const |
Returns name of class to which the object belongs. | |
virtual void | Delete (Option_t *option="") |
Delete this object. | |
virtual Int_t | DistancetoPrimitive (Int_t px, Int_t py) |
Computes distance from point (px,py) to the object. | |
virtual void | Draw (Option_t *option="") |
Default Draw method for all objects. | |
virtual void | DrawClass () const |
Draw class inheritance tree of the class to which this object belongs. | |
virtual TObject * | DrawClone (Option_t *option="") const |
Draw a clone of this object in the current selected pad with: gROOT->SetSelectedPad(c1) . | |
virtual void | Dump () const |
Dump contents of object on stdout. | |
virtual void | Error (const char *method, const char *msgfmt,...) const |
Issue error message. | |
virtual void | Execute (const char *method, const char *params, Int_t *error=nullptr) |
Execute method on this object with the given parameter string, e.g. | |
virtual void | Execute (TMethod *method, TObjArray *params, Int_t *error=nullptr) |
Execute method on this object with parameters stored in the TObjArray. | |
virtual void | ExecuteEvent (Int_t event, Int_t px, Int_t py) |
Execute action corresponding to an event at (px,py). | |
virtual void | Fatal (const char *method, const char *msgfmt,...) const |
Issue fatal error message. | |
virtual TObject * | FindObject (const char *name) const |
Must be redefined in derived classes. | |
virtual TObject * | FindObject (const TObject *obj) const |
Must be redefined in derived classes. | |
virtual Option_t * | GetDrawOption () const |
Get option used by the graphics system to draw this object. | |
virtual const char * | GetIconName () const |
Returns mime type name of object. | |
virtual char * | GetObjectInfo (Int_t px, Int_t py) const |
Returns string containing info about the object at position (px,py). | |
virtual Option_t * | GetOption () const |
virtual UInt_t | GetUniqueID () const |
Return the unique object id. | |
virtual Bool_t | HandleTimer (TTimer *timer) |
Execute action in response of a timer timing out. | |
Bool_t | HasInconsistentHash () const |
Return true is the type of this object is known to have an inconsistent setup for Hash and RecursiveRemove (i.e. | |
virtual void | Info (const char *method, const char *msgfmt,...) const |
Issue info message. | |
virtual Bool_t | InheritsFrom (const char *classname) const |
Returns kTRUE if object inherits from class "classname". | |
virtual Bool_t | InheritsFrom (const TClass *cl) const |
Returns kTRUE if object inherits from TClass cl. | |
virtual void | Inspect () const |
Dump contents of this object in a graphics canvas. | |
void | InvertBit (UInt_t f) |
Bool_t | IsDestructed () const |
IsDestructed. | |
virtual Bool_t | IsEqual (const TObject *obj) const |
Default equal comparison (objects are equal if they have the same address in memory). | |
virtual Bool_t | IsFolder () const |
Returns kTRUE in case object contains browsable objects (like containers or lists of other objects). | |
R__ALWAYS_INLINE Bool_t | IsOnHeap () const |
R__ALWAYS_INLINE Bool_t | IsZombie () const |
void | MayNotUse (const char *method) const |
Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary). | |
virtual Bool_t | Notify () |
This method must be overridden to handle object notification (the base implementation is no-op). | |
void | Obsolete (const char *method, const char *asOfVers, const char *removedFromVers) const |
Use this method to declare a method obsolete. | |
void | operator delete (void *ptr) |
Operator delete. | |
void | operator delete (void *ptr, void *vp) |
Only called by placement new when throwing an exception. | |
void | operator delete[] (void *ptr) |
Operator delete []. | |
void | operator delete[] (void *ptr, void *vp) |
Only called by placement new[] when throwing an exception. | |
void * | operator new (size_t sz) |
void * | operator new (size_t sz, void *vp) |
void * | operator new[] (size_t sz) |
void * | operator new[] (size_t sz, void *vp) |
TObject & | operator= (const TObject &rhs) |
TObject assignment operator. | |
virtual void | Paint (Option_t *option="") |
This method must be overridden if a class wants to paint itself. | |
virtual void | Pop () |
Pop on object drawn in a pad to the top of the display list. | |
virtual Int_t | Read (const char *name) |
Read contents of object with specified name from the current directory. | |
virtual void | RecursiveRemove (TObject *obj) |
Recursively remove this object from a list. | |
void | ResetBit (UInt_t f) |
virtual void | SaveAs (const char *filename="", Option_t *option="") const |
Save this object in the file specified by filename. | |
virtual void | SavePrimitive (std::ostream &out, Option_t *option="") |
Save a primitive as a C++ statement(s) on output stream "out". | |
void | SetBit (UInt_t f) |
void | SetBit (UInt_t f, Bool_t set) |
Set or unset the user status bits as specified in f. | |
virtual void | SetDrawOption (Option_t *option="") |
Set drawing option for object. | |
virtual void | SetUniqueID (UInt_t uid) |
Set the unique object id. | |
void | StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b) |
virtual void | SysError (const char *method, const char *msgfmt,...) const |
Issue system error message. | |
R__ALWAYS_INLINE Bool_t | TestBit (UInt_t f) const |
Int_t | TestBits (UInt_t f) const |
virtual void | UseCurrentStyle () |
Set current style settings in this object This function is called when either TCanvas::UseCurrentStyle or TROOT::ForceStyle have been invoked. | |
virtual void | Warning (const char *method, const char *msgfmt,...) const |
Issue warning message. | |
virtual Int_t | Write (const char *name=nullptr, Int_t option=0, Int_t bufsize=0) |
Write this object to the current directory. | |
virtual Int_t | Write (const char *name=nullptr, Int_t option=0, Int_t bufsize=0) const |
Write this object to the current directory. | |
Static Public Member Functions | |
static TClass * | Class () |
static const char * | Class_Name () |
static constexpr Version_t | Class_Version () |
static const char * | DeclFileName () |
Static Public Member Functions inherited from RooStats::IntervalCalculator | |
static TClass * | Class () |
static const char * | Class_Name () |
static constexpr Version_t | Class_Version () |
static const char * | DeclFileName () |
Static Public Member Functions inherited from TNamed | |
static TClass * | Class () |
static const char * | Class_Name () |
static constexpr Version_t | Class_Version () |
static const char * | DeclFileName () |
Static Public Member Functions inherited from TObject | |
static TClass * | Class () |
static const char * | Class_Name () |
static constexpr Version_t | Class_Version () |
static const char * | DeclFileName () |
static Longptr_t | GetDtorOnly () |
Return destructor only flag. | |
static Bool_t | GetObjectStat () |
Get status of object stat flag. | |
static void | SetDtorOnly (void *obj) |
Set destructor only flag. | |
static void | SetObjectStat (Bool_t stat) |
Turn on/off tracking of objects in the TObjectTable. | |
Protected Member Functions | |
void | ApproximatePosterior () const |
approximate posterior in nbins using a TF1 scan the poi values and evaluate the posterior at each point and save the result in a cloned TF1 For each point the posterior is evaluated by integrating the nuisance parameters | |
void | ClearAll () const |
clear all cached pdf objects | |
void | ComputeIntervalFromApproxPosterior (double c1, double c2) const |
compute the interval using the approximate posterior function | |
void | ComputeIntervalFromCdf (double c1, double c2) const |
internal function compute the interval using Cdf integration | |
void | ComputeIntervalUsingRooFit (double c1, double c2) const |
internal function compute the interval using RooFit | |
void | ComputeShortestInterval () const |
compute the shortest interval from the histogram representing the posterior | |
Protected Member Functions inherited from TObject | |
virtual void | DoError (int level, const char *location, const char *fmt, va_list va) const |
Interface to ErrorHandler (protected). | |
void | MakeZombie () |
Private Attributes | |
TF1 * | fApproxPosterior |
TF1 representing the scanned posterior function. | |
double | fBrfPrecision |
root finder precision | |
RooArgSet | fConditionalObs |
conditional observables | |
RooAbsData * | fData |
data set | |
RooArgSet | fGlobalObs |
global observables | |
RooAbsReal * | fIntegratedLikelihood |
integrated likelihood function, i.e - unnormalized posterior function | |
TString | fIntegrationType |
double | fLeftSideFraction |
fraction of probability content on left side of interval | |
RooAbsReal * | fLikelihood |
internal pointer to likelihood function | |
std::unique_ptr< RooAbsReal > | fLogLike |
internal pointer to log likelihood function | |
double | fLower |
computer lower interval bound | |
double | fNLLMin |
minimum value of Nll | |
int | fNScanBins |
number of bins to scan, if = -1 no scan is done (default) | |
RooArgSet | fNuisanceParameters |
nuisance parameters | |
RooAbsPdf * | fNuisancePdf |
nuisance pdf (needed when using nuisance sampling technique) | |
int | fNumIterations |
number of iterations (when using ToyMC) | |
RooAbsPdf * | fPdf |
model pdf (could contain the nuisance pdf as constraint term) | |
RooArgSet | fPOI |
POI. | |
ROOT::Math::IGenFunction * | fPosteriorFunction |
function representing the posterior | |
RooAbsPdf * | fPosteriorPdf |
normalized (on the poi) posterior pdf | |
RooAbsPdf * | fPriorPdf |
prior pdf (typically for the POI) | |
RooAbsPdf * | fProductPdf |
internal pointer to model * prior | |
double | fSize |
size used for getting the interval | |
double | fUpper |
upper interval bound | |
bool | fValidInterval |
Additional Inherited Members | |
Public Types inherited from TObject | |
enum | { kIsOnHeap = 0x01000000 , kNotDeleted = 0x02000000 , kZombie = 0x04000000 , kInconsistent = 0x08000000 , kBitMask = 0x00ffffff } |
enum | { kSingleKey = (1ULL << ( 0 )) , kOverwrite = (1ULL << ( 1 )) , kWriteDelete = (1ULL << ( 2 )) } |
enum | EDeprecatedStatusBits { kObjInCanvas = (1ULL << ( 3 )) } |
enum | EStatusBits { kCanDelete = (1ULL << ( 0 )) , kMustCleanup = (1ULL << ( 3 )) , kIsReferenced = (1ULL << ( 4 )) , kHasUUID = (1ULL << ( 5 )) , kCannotPick = (1ULL << ( 6 )) , kNoContextMenu = (1ULL << ( 8 )) , kInvalidObject = (1ULL << ( 13 )) } |
Protected Types inherited from TObject | |
enum | { kOnlyPrepStep = (1ULL << ( 3 )) } |
Protected Attributes inherited from TNamed | |
TString | fName |
TString | fTitle |
#include <RooStats/BayesianCalculator.h>
RooStats::BayesianCalculator::BayesianCalculator | ( | ) |
RooStats::BayesianCalculator::BayesianCalculator | ( | RooAbsData & | data, |
RooAbsPdf & | pdf, | ||
const RooArgSet & | POI, | ||
RooAbsPdf & | priorPdf, | ||
const RooArgSet * | nuisanceParameters = nullptr |
||
) |
Constructor from data set, model pdf, parameter of interests and prior pdf If nuisance parameters are given they will be integrated according either to the prior or their constraint term included in the model.
Definition at line 661 of file BayesianCalculator.cxx.
RooStats::BayesianCalculator::BayesianCalculator | ( | RooAbsData & | data, |
ModelConfig & | model | ||
) |
Constructor from a data set and a ModelConfig model pdf, poi and nuisances will be taken from the ModelConfig.
Definition at line 692 of file BayesianCalculator.cxx.
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override |
destructor
Definition at line 712 of file BayesianCalculator.cxx.
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protected |
approximate posterior in nbins using a TF1 scan the poi values and evaluate the posterior at each point and save the result in a cloned TF1 For each point the posterior is evaluated by integrating the nuisance parameters
Definition at line 1325 of file BayesianCalculator.cxx.
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static |
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inlinestaticconstexpr |
Definition at line 194 of file BayesianCalculator.h.
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protected |
clear all cached pdf objects
Definition at line 721 of file BayesianCalculator.cxx.
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protected |
compute the interval using the approximate posterior function
Definition at line 1370 of file BayesianCalculator.cxx.
internal function compute the interval using Cdf integration
Definition at line 1249 of file BayesianCalculator.cxx.
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protected |
internal function compute the interval using RooFit
Definition at line 1200 of file BayesianCalculator.cxx.
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protected |
compute the shortest interval from the histogram representing the posterior
Definition at line 1391 of file BayesianCalculator.cxx.
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inlineoverridevirtual |
Get the Confidence level for the test.
Implements RooStats::IntervalCalculator.
Definition at line 108 of file BayesianCalculator.h.
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inlinestatic |
Definition at line 194 of file BayesianCalculator.h.
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inline |
Definition at line 142 of file BayesianCalculator.h.
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overridevirtual |
compute the interval.
Compute the interval.
By Default a central interval is computed By using SetLeftTileFraction can control if central/ upper/lower interval For shortest interval use SetShortestInterval(true)
By Default a central interval is computed and the result is a SimpleInterval object.
Using the method (to be called before SetInterval) SetLeftSideTailFraction the user can choose the type of interval. By default the returned interval is a central interval with the confidence level specified previously in the constructor ( LeftSideTailFraction = 0.5).
NOTE: The BayesianCalculator covers only the case with one single parameter of interest
NOTE: User takes ownership of the returned object
Implements RooStats::IntervalCalculator.
Definition at line 1102 of file BayesianCalculator.cxx.
double RooStats::BayesianCalculator::GetMode | ( | ) | const |
return the mode (most probable value of the posterior function)
Returns the value of the parameter for the point in parameter-space that is the most likely.
How do we do if there are points that are equi-probable? use approximate posterior t.b.d use real function to find the mode
Definition at line 1189 of file BayesianCalculator.cxx.
RooAbsReal * RooStats::BayesianCalculator::GetPosteriorFunction | ( | ) | const |
return posterior function (object is managed by the BayesianCalculator class)
Build and return the posterior function (not normalized) as a RooAbsReal the posterior is obtained from the product of the likelihood function and the prior pdf which is then integrated in the nuisance parameters (if existing).
A prior function for the nuisance can be specified either in the prior pdf object or in the model itself. If no prior nuisance is specified, but prior parameters are then the integration is performed assuming a flat prior for the nuisance parameters.
NOTE: the return object is managed by the BayesianCalculator class, users do not need to delete it, but the object will be deleted when the BayesiabCalculator object is deleted
Definition at line 776 of file BayesianCalculator.cxx.
TH1 * RooStats::BayesianCalculator::GetPosteriorHistogram | ( | ) | const |
return the approximate posterior as histogram (TH1 object). Note the object is managed by the BayesianCalculator class
When am approximate posterior is computed binninig the parameter of interest (poi) range (see SetScanOfPosteriors) an histogram is created and can be returned to the user A nullptr is instead returned when the posterior is computed without binning the poi.
NOTE: the returned object is managed by the BayesianCalculator class, if the user wants to take ownership of the returned histogram, he needs to clone or copy the return object.
Definition at line 998 of file BayesianCalculator.cxx.
RooAbsPdf * RooStats::BayesianCalculator::GetPosteriorPdf | ( | ) | const |
return posterior pdf (object is managed by the user)
Build and return the posterior pdf (i.e posterior function normalized to all range of poi) Note that an extra integration in the POI is required for the normalization NOTE: user must delete the returned object.
Definition at line 974 of file BayesianCalculator.cxx.
RooPlot * RooStats::BayesianCalculator::GetPosteriorPlot | ( | bool | norm = false , |
double | precision = 0.01 |
||
) | const |
get the plot with option to get it normalized
return a RooPlot with the posterior and the credibility region NOTE: User takes ownership of the returned object
Definition at line 1008 of file BayesianCalculator.cxx.
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inlineoverridevirtual |
Reimplemented from RooStats::IntervalCalculator.
Definition at line 194 of file BayesianCalculator.h.
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inline |
set the precision of the Root Finder
Definition at line 121 of file BayesianCalculator.h.
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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
Definition at line 92 of file BayesianCalculator.h.
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inlineoverridevirtual |
set the confidence level for the interval (eg. 0.95 for a 95% Confidence Interval)
Implements RooStats::IntervalCalculator.
Definition at line 104 of file BayesianCalculator.h.
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inlineoverridevirtual |
Set the DataSet ( add to the workspace if not already there ?)
Implements RooStats::IntervalCalculator.
Definition at line 72 of file BayesianCalculator.h.
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inlinevirtual |
set the global observables which will be used when creating the NLL so the constraint pdf's will be normalized correctly on the global observables when computing the NLL
Definition at line 96 of file BayesianCalculator.h.
void RooStats::BayesianCalculator::SetIntegrationType | ( | const char * | type | ) |
set the integration type (possible type are) :
Extra integration types are:
Definition at line 1080 of file BayesianCalculator.cxx.
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inline |
set the fraction of probability content on the left tail Central limits use 0.5 (default case) for upper limits it is 0 and 1 for lower limit For shortest intervals a negative value (i.e.
-1) must be given
Definition at line 114 of file BayesianCalculator.h.
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overridevirtual |
set the model via the ModelConfig
set the model to use The model pdf, prior pdf, parameter of interest and nuisances will be taken according to the model
Implements RooStats::IntervalCalculator.
Definition at line 745 of file BayesianCalculator.cxx.
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inlinevirtual |
specify the nuisance parameters (eg. the rest of the parameters)
Definition at line 85 of file BayesianCalculator.h.
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inlinevirtual |
set the number of iterations when running a MC integration algorithm If not set use default algorithmic values In case of ToyMC sampling of the nuisance the value is 100 In case of using the GSL MCintegrations types the default value is defined in ROOT::Math::IntegratorMultiDimOptions::DefaultNCalls()
Definition at line 133 of file BayesianCalculator.h.
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inlinevirtual |
specify the parameters of interest in the interval
Definition at line 82 of file BayesianCalculator.h.
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inlinevirtual |
Set only the Prior Pdf.
Definition at line 88 of file BayesianCalculator.h.
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inline |
use directly the approximate posterior function obtained by binning it in nbins by default the cdf is used by integrating the posterior if a value of nbin <= 0 the cdf function will be used
Definition at line 126 of file BayesianCalculator.h.
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inline |
set the Bayesian calculator to compute the shortest interval (default is central interval) to switch off SetLeftSideTailFraction to the right value
Definition at line 118 of file BayesianCalculator.h.
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inlineoverridevirtual |
set the size of the test (rate of Type I error) ( Eg. 0.05 for a 95% Confidence Interval)
Implements RooStats::IntervalCalculator.
Definition at line 99 of file BayesianCalculator.h.
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inlineoverridevirtual |
Get the size of the test (eg. rate of Type I error)
Implements RooStats::IntervalCalculator.
Definition at line 106 of file BayesianCalculator.h.
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overridevirtual |
Reimplemented from RooStats::IntervalCalculator.
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inline |
Definition at line 194 of file BayesianCalculator.h.
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mutableprivate |
TF1 representing the scanned posterior function.
Definition at line 179 of file BayesianCalculator.h.
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private |
root finder precision
Definition at line 185 of file BayesianCalculator.h.
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private |
conditional observables
Definition at line 170 of file BayesianCalculator.h.
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private |
data set
Definition at line 164 of file BayesianCalculator.h.
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private |
global observables
Definition at line 171 of file BayesianCalculator.h.
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mutableprivate |
integrated likelihood function, i.e - unnormalized posterior function
Definition at line 176 of file BayesianCalculator.h.
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private |
Definition at line 190 of file BayesianCalculator.h.
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private |
fraction of probability content on left side of interval
Definition at line 184 of file BayesianCalculator.h.
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mutableprivate |
internal pointer to likelihood function
Definition at line 175 of file BayesianCalculator.h.
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mutableprivate |
internal pointer to log likelihood function
Definition at line 174 of file BayesianCalculator.h.
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mutableprivate |
computer lower interval bound
Definition at line 180 of file BayesianCalculator.h.
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mutableprivate |
minimum value of Nll
Definition at line 182 of file BayesianCalculator.h.
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mutableprivate |
number of bins to scan, if = -1 no scan is done (default)
Definition at line 186 of file BayesianCalculator.h.
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private |
nuisance parameters
Definition at line 169 of file BayesianCalculator.h.
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private |
nuisance pdf (needed when using nuisance sampling technique)
Definition at line 168 of file BayesianCalculator.h.
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private |
number of iterations (when using ToyMC)
Definition at line 187 of file BayesianCalculator.h.
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private |
model pdf (could contain the nuisance pdf as constraint term)
Definition at line 165 of file BayesianCalculator.h.
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private |
POI.
Definition at line 166 of file BayesianCalculator.h.
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mutableprivate |
function representing the posterior
Definition at line 178 of file BayesianCalculator.h.
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mutableprivate |
normalized (on the poi) posterior pdf
Definition at line 177 of file BayesianCalculator.h.
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private |
prior pdf (typically for the POI)
Definition at line 167 of file BayesianCalculator.h.
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mutableprivate |
internal pointer to model * prior
Definition at line 173 of file BayesianCalculator.h.
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private |
size used for getting the interval
Definition at line 183 of file BayesianCalculator.h.
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mutableprivate |
upper interval bound
Definition at line 181 of file BayesianCalculator.h.
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mutableprivate |
Definition at line 188 of file BayesianCalculator.h.