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RatioOfProfiledLikelihoodsTestStat.h
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1// @(#)root/roostats:$Id$
2// Authors: Kyle Cranmer, Sven Kreiss June 2010
3/*************************************************************************
4 * Copyright (C) 1995-2008, Rene Brun and Fons Rademakers. *
5 * All rights reserved. *
6 * *
7 * For the licensing terms see $ROOTSYS/LICENSE. *
8 * For the list of contributors see $ROOTSYS/README/CREDITS. *
9 *************************************************************************/
10
11#ifndef ROOSTATS_RatioOfProfiledLikelihoodsTestStat
12#define ROOSTATS_RatioOfProfiledLikelihoodsTestStat
13
14
15#include "Rtypes.h"
16
17#include "RooNLLVar.h"
18
20
22
23
24namespace RooStats {
25
27
28 public:
29
33 fAltPOI(NULL),
34 fSubtractMLE(true),
36 fDetailedOutput(NULL)
37 {
38 // Proof constructor. Don't use.
39 }
40
42 const RooArgSet* altPOI=0) :
43 fNullProfile(nullPdf),
44 fAltProfile(altPdf),
45 fSubtractMLE(true),
47 fDetailedOutput(NULL)
48 {
49 // Calculates the ratio of profiled likelihoods.
50
51 if(altPOI)
52 fAltPOI = (RooArgSet*) altPOI->snapshot();
53 else
54 fAltPOI = new RooArgSet(); // empty set
55
56 }
57
58 //__________________________________________
60 if(fAltPOI) delete fAltPOI;
62 }
63
64
65 // returns -logL(poi, conditional MLE of nuisance params)
66 // it does not subtract off the global MLE
67 // because nuisance parameters of null and alternate may not
68 // be the same.
70
71 // evaluate the ratio of profile likelihood
72 virtual Double_t Evaluate(RooAbsData& data, RooArgSet& nullParamsOfInterest);
73
74 virtual void EnableDetailedOutput( bool e=true ) {
78 }
79
80 static void SetAlwaysReuseNLL(Bool_t flag);
81
82 void SetReuseNLL(Bool_t flag) {
85 }
86
87 void SetMinimizer(const char* minimizer){
88 fNullProfile.SetMinimizer(minimizer);
89 fAltProfile.SetMinimizer(minimizer);
90 }
91 void SetStrategy(Int_t strategy){
92 fNullProfile.SetStrategy(strategy);
93 fAltProfile.SetStrategy(strategy);
94 }
98 }
99 void SetPrintLevel(Int_t printLevel){
100 fNullProfile.SetPrintLevel(printLevel);
101 fAltProfile.SetPrintLevel(printLevel);
102 }
103
104 // set the conditional observables which will be used when creating the NLL
105 // so the pdf's will not be normalized on the conditional observables when computing the NLL
106 virtual void SetConditionalObservables(const RooArgSet& set) {
109 }
110
111 // set the global observables which will be used when creating the NLL
112 // so the constraint pdf's will be normalized correctly on the global observables when computing the NLL
113 virtual void SetGlobalObservables(const RooArgSet& set) {
116 }
117
118 virtual const RooArgSet* GetDetailedOutput(void) const {
119 // Returns detailed output. The value returned by this function is updated after each call to Evaluate().
120 // The returned RooArgSet contains the following for the alternative and null hypotheses:
121 // - the minimum nll, fitstatus and convergence quality for each fit
122 // - for each fit and for each non-constant parameter, the value, error and pull of the parameter are stored
123 return fDetailedOutput;
124 }
125
126
127
128
129 virtual const TString GetVarName() const { return "log(L(#mu_{1},#hat{#nu}_{1}) / L(#mu_{0},#hat{#nu}_{0}))"; }
130
131 // const bool PValueIsRightTail(void) { return false; } // overwrites default
132
133 void SetSubtractMLE(bool subtract){fSubtractMLE = subtract;}
134
135 private:
136
139
143
146
147
148 protected:
149 ClassDef(RatioOfProfiledLikelihoodsTestStat,3) // implements the ratio of profiled likelihood as test statistic
150 };
151
152}
153
154
155#endif
#define e(i)
Definition: RSha256.hxx:103
int Int_t
Definition: RtypesCore.h:43
bool Bool_t
Definition: RtypesCore.h:61
double Double_t
Definition: RtypesCore.h:57
#define ClassDef(name, id)
Definition: Rtypes.h:322
RooAbsData is the common abstract base class for binned and unbinned datasets.
Definition: RooAbsData.h:44
RooArgSet is a container object that can hold multiple RooAbsArg objects.
Definition: RooArgSet.h:28
RooArgSet * snapshot(bool deepCopy=true) const
Use RooAbsCollection::snapshot(), but return as RooArgSet.
Definition: RooArgSet.h:126
ProfileLikelihoodTestStat is an implementation of the TestStatistic interface that calculates the pro...
virtual void SetConditionalObservables(const RooArgSet &set)
interface to set conditional observables. If a test statistics needs them it will re-implement this f...
virtual void EnableDetailedOutput(bool e=true, bool withErrorsAndPulls=false)
virtual void SetGlobalObservables(const RooArgSet &set)
interface to set global observables. If a test statistics needs them it will re-implement this functi...
TestStatistic that returns the ratio of profiled likelihoods.
virtual const RooArgSet * GetDetailedOutput(void) const
return detailed output: for fits this can be pulls, processing time, ... The returned pointer will no...
virtual void SetGlobalObservables(const RooArgSet &set)
interface to set global observables. If a test statistics needs them it will re-implement this functi...
RatioOfProfiledLikelihoodsTestStat(RooAbsPdf &nullPdf, RooAbsPdf &altPdf, const RooArgSet *altPOI=0)
Double_t ProfiledLikelihood(RooAbsData &data, RooArgSet &poi, RooAbsPdf &pdf)
returns -logL(poi, conditional MLE of nuisance params) subtract off the global MLE or not depending o...
virtual void SetConditionalObservables(const RooArgSet &set)
interface to set conditional observables. If a test statistics needs them it will re-implement this f...
virtual Double_t Evaluate(RooAbsData &data, RooArgSet &nullParamsOfInterest)
evaluate the ratio of profile likelihood
TestStatistic is an interface class to provide a facility for construction test statistics distributi...
Definition: TestStatistic.h:31
Basic string class.
Definition: TString.h:131
Namespace for the RooStats classes.
Definition: Asimov.h:19