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Reference Guide
Zbi_Zgamma.C File Reference

Detailed Description

View in nbviewer Open in SWAN Demonstrate Z_Bi = Z_Gamma

pict1_Zbi_Zgamma.C.png
RooFit v3.60 -- Developed by Wouter Verkerke and David Kirkby
Copyright (C) 2000-2013 NIKHEF, University of California & Stanford University
All rights reserved, please read http://roofit.sourceforge.net/license.txt
[#1] INFO:ObjectHandling -- RooWorkspace::exportToCint(w) INFO: references to all objects in this workspace will be created in CINT in 'namespace w'
[#1] INFO:NumericIntegration -- RooRealIntegral::init([py_X_prior_b]_Norm[b]_denominator_Int[b]) using numeric integrator RooIntegrator1D to calculate Int(b)
[#1] INFO:NumericIntegration -- RooRealIntegral::init([py_X_prior_b]_Int[b]) using numeric integrator RooIntegrator1D to calculate Int(b)
[#1] INFO:NumericIntegration -- RooRealIntegral::init([py_X_prior_b]_Norm[b]_denominator_Int[b]) using numeric integrator RooIntegrator1D to calculate Int(b)
[#1] INFO:NumericIntegration -- RooRealIntegral::init([[py_X_prior_b]_Norm[b]_X_px_NORM[x]]_Int[b]) using numeric integrator RooIntegrator1D to calculate Int(b)
[#1] INFO:NumericIntegration -- RooRealIntegral::init([py_X_prior_b]_Norm[b]_denominator_Int[b]) using numeric integrator RooIntegrator1D to calculate Int(b)
[#1] INFO:NumericIntegration -- RooRealIntegral::init([py_X_prior_b]_Int[b]) using numeric integrator RooIntegrator1D to calculate Int(b)
[#1] INFO:NumericIntegration -- RooRealIntegral::init([py_X_prior_b]_Norm[b]_denominator_Int[b]) using numeric integrator RooIntegrator1D to calculate Int(b)
[#1] INFO:NumericIntegration -- RooRealIntegral::init([py_X_prior_b_X_px]_Norm[b]_denominator_Int[b]) using numeric integrator RooIntegrator1D to calculate Int(b)
[#1] INFO:NumericIntegration -- RooRealIntegral::init([py_X_prior_b]_Norm[b]_denominator_Int[b]) using numeric integrator RooIntegrator1D to calculate Int(b)
[#1] INFO:NumericIntegration -- RooRealIntegral::init([py_X_prior_b]_Int[b]) using numeric integrator RooIntegrator1D to calculate Int(b)
[#1] INFO:NumericIntegration -- RooRealIntegral::init([py_X_prior_b]_Norm[b]_denominator_Int[b]) using numeric integrator RooIntegrator1D to calculate Int(b)
[#1] INFO:NumericIntegration -- RooRealIntegral::init([py_X_prior_b]_Norm[b]_denominator_Int[b]) using numeric integrator RooIntegrator1D to calculate Int(b)
[#1] INFO:NumericIntegration -- RooRealIntegral::init([py_X_prior_b]_Int[b]) using numeric integrator RooIntegrator1D to calculate Int(b)
[#1] INFO:NumericIntegration -- RooRealIntegral::init([[py_X_prior_b]_Norm[b]_X_px_cdf_NORM[x_prime]]_Int[b]) using numeric integrator RooIntegrator1D to calculate Int(b)
[#1] INFO:NumericIntegration -- RooRealIntegral::init([[py_X_prior_b]_Norm[b]_X_px_cdf_Int[x_prime|CDF]_Norm[x_prime]]_Int[b|CDF]) using numeric integrator RooIntegrator1D to calculate Int(b)
Hybrid p-value = 0.999226
Z_Gamma Significance = 3.1655
Z_Bi significance estimation: 3.10804
#include "RooRealVar.h"
#include "RooProdPdf.h"
#include "RooWorkspace.h"
#include "RooDataSet.h"
#include "TCanvas.h"
#include "TH1.h"
using namespace RooFit;
using namespace RooStats;
void Zbi_Zgamma()
{
// Make model for prototype on/off problem
// Pois(x | s+b) * Pois(y | tau b )
// for Z_Gamma, use uniform prior on b.
RooWorkspace *w1 = new RooWorkspace("w", true);
w1->factory("Poisson::px(x[150,0,500],sum::splusb(s[0,0,100],b[100,0,300]))");
w1->factory("Poisson::py(y[100,0,500],prod::taub(tau[1.],b))");
w1->factory("Uniform::prior_b(b)");
// construct the Bayesian-averaged model (eg. a projection pdf)
// p'(x|s) = \int db p(x|s+b) * [ p(y|b) * prior(b) ]
w1->factory("PROJ::averagedModel(PROD::foo(px|b,py,prior_b),b)");
// plot it, blue is averaged model, red is b known exactly
RooPlot *frame = w1->var("x")->frame();
w1->pdf("averagedModel")->plotOn(frame);
w1->pdf("px")->plotOn(frame, LineColor(kRed));
frame->Draw();
// compare analytic calculation of Z_Bi
// with the numerical RooFit implementation of Z_Gamma
// for an example with x = 150, y = 100
// numeric RooFit Z_Gamma
w1->var("y")->setVal(100);
w1->var("x")->setVal(150);
RooAbsReal *cdf = w1->pdf("averagedModel")->createCdf(*w1->var("x"));
cdf->getVal(); // get ugly print messages out of the way
cout << "Hybrid p-value = " << cdf->getVal() << endl;
cout << "Z_Gamma Significance = " << PValueToSignificance(1 - cdf->getVal()) << endl;
// analytic Z_Bi
double Z_Bi = NumberCountingUtils::BinomialWithTauObsZ(150, 100, 1);
std::cout << "Z_Bi significance estimation: " << Z_Bi << std::endl;
// OUTPUT
// Hybrid p-value = 0.999058
// Z_Gamma Significance = 3.10804
// Z_Bi significance estimation: 3.10804
}
Author
Kyle Cranmer & Wouter Verkerke

Definition in file Zbi_Zgamma.C.