#include <AsymptoticExclusion.h>

Inheritance diagram for AsymptoticExclusion:

Public Member Functions
	AsymptoticExclusion (ProfileLikelihood *pl, double confidenceLevel)

ProfileLikelihood *	getProfileLikelihood ()

TGraphAsymmErrors	getExpectedMedian ()

TGraphAsymmErrors	getExpected2Sigma ()

TGraph	getObservedLimit ()

double	getMass ()

void	generateAndSetAsimov (double mu_prime)

void	setRealData ()

void	setToyDataset (double seed, double mu_prime)

double	computeQTestStat (double mu, bool useStoredFit=false)

void	computeSensitivity ()

double	computeSensitivityHagar ()

double	computeExpectedLimit (double sigma_0, double N, double CL)

double	conditionalFit (double mu)

double	unconditionalFit ()

double	getMu_hat ()

double	computeSigmaAsimov (double mu_prime)

void	setNscanPoints (int nPoints)

void	writeToFile (TString prefix="limit_")

TGraph	getSigmaScan ()

TGraph	getqTestScan ()

void	computeLimits ()

double	compute_pval_s_plus_b (double q_obs)

double	compute_pval_b (double q_obs, double mu_val, double sigma_val)

void	setScanMin (double mi)

void	setScanMax (double ma)

void	LikelihoodScan ()

void	setQTilde (bool doSet)

void	setAlternativeXAxisVal (double x)

void	setAlternative2DHistoRange (int Nx, double xmin, double xmax, int Ny, double ymin, double ymax)

TGraph	getqTestScanData ()

double	getObsLimitCLS ()

double	getObsLimitnoCLS ()

Public Member Functions inherited from XeStat
	XeStat (TString name)

void	setName (TString nam="No_Name")
	helper method to set the name of this instance.

TString	getName ()
	helper method to return the name of this instance.

void	setExperiment (int exp)
	set the experiment number, usefull for combination

int	getExperiment ()
	set the experiment number, usefull for combination

Public Member Functions inherited from errorHandler
	errorHandler (TString name)

void	Error (TString functionName, TString message)
	Send an Error message to the user. More...

void	Warning (TString functionName, TString message)
	Send a Warning message to the user. More...

void	Info (TString functionName, TString message)
	Send an Info message to the user. More...

void	Debug (TString functionName, TString message)
	Send a Debug message to the user. More...

void	setPrintLevel (int level)
	Set the local printing level (for this instance only) More...

int	getPrintLevel ()
	Return the current print level for this instance. remind that if you set with setPrintLevel this will override the global print level.

Public Member Functions inherited from printTools
	printTools ()
	---------— Print Toools -----------— ///

Additional Inherited Members
Static Public Member Functions inherited from XeStat
static void	setAnalysisMode (int mode)

static int	getAnalysisMode ()

static bool	checkAnalysisMode (TString name, int requested)

static bool	isAnalysisDefined (bool verbose=false)

static bool	isCutsBased ()

static bool	isPL ()

static int	getSigmaLinLog (int unit)

static TString	getAnalysisModeName ()

static TString	getAnalysisModeName (int mode)

static TString	getSystematicModeName (int syst)

static TString	getSigmaUnitName (int unit)

static TString	getSigmaLabel (int unit)

static TString	getSigmaModeName (int mode)

static TString	getUpperSigmaLabel (int unit)

Static Public Member Functions inherited from printTools
static TString	upperCase (TString s)

static TString	lowerCase (TString s)

static TString	trim (TString s)

static TString	justify (TString s, int w, bool left, bool trim)

static TString	rightJustify (TString s, int w, bool trim=false)

static TString	leftJustify (TString s, int w, bool trim=false)

static TString	format0I (int v, int w=1)

static TString	formatLI (int v, int w=1, int p=1)

static TString	formatRI (int v, int w=1, int p=1)

static TString	formatF (double v, int w=1, int p=1)

static TString	formatR (double v, int w=1, int p=1)

static TString	formatLF (double v, int w=1, int p=1)

static TString	formatRF (double v, int w=1, int p=1)

static TString	formatG (double v, int w=1, int p=1)

static TString	formatLG (double v, int w=1, int p=1)

static TString	formatRG (double v, int w=1, int p=1)

static TString	formatI (int v, int w=1, int trailer=0)

static TString	doOrDont (bool b)

Public Attributes inherited from errorHandler
int	localPrintLevel

TString	className

Static Public Attributes inherited from errorHandler
static int	globalPrintLevel = 1

Protected Attributes inherited from XeStat
TString	name

int	experiment

Static Protected Attributes inherited from XeStat
static int	analysisMode = NO_ANALYSIS

Detailed Description

Computes limits with the asymptotic formulae, default is CLs. Output: root files with histograms for a single mass point, several files can be hadd togheter. This is to promote parallelization. The mass point has to be defined previously using the appropriated XeRun method

Member Function Documentation

◆ compute_pval_s_plus_b()

double AsymptoticExclusion::compute_pval_s_plus_b ( double q_obs )

Compute pvalues

◆ computeExpectedLimit()

double AsymptoticExclusion::computeExpectedLimit	(	double	sigma_0,
		double	N,
		double	CL
	)

Limit wrapper formula, this is based on the "asymptotic paper" formula 89, and includes CLs. returns the limit for the specified band (zero in case of median) in terms of the signal strenght.

Parameters

sigma,is	the asimov sigma related to mu =0
CL,confidence	level
N,sigma	band, can take positive and negative value

◆ computeLimits()

void AsymptoticExclusion::computeLimits ( )

Compute Observed limit with CLs and asymptotics

LOOP over values of mu within a defined range, the range and steps are defined in computeSetAsimovSigma()

◆ computeQTestStat()

double AsymptoticExclusion::computeQTestStat	(	double	mu,
		bool	useStoredFit = `false`
	)

Compute the value of the test statistic q_tilde for a given signal strenght mu.

Parameters

useStoredFit impose to use the conditional fit outcome already computed, usefull when computing limits with data.

◆ computeSensitivity()

void AsymptoticExclusion::computeSensitivity ( )

Compute the expected CLs limits with bands. It stores it in the graphs getExpectedMedian ecc..

◆ computeSensitivityHagar()

double AsymptoticExclusion::computeSensitivityHagar ( )

better way of producing sensitivity

◆ computeSigmaAsimov()

double AsymptoticExclusion::computeSigmaAsimov ( double mu_prime )

Compute the variance of sigma_hut around sigma_true with Asimov dataset

Parameters

mu_prime,true assumed value of signal strenght

◆ conditionalFit()

double AsymptoticExclusion::conditionalFit ( double mu )

returns the log(likelihood(mu,theta)) for the conditional fit with signal strenght mu

◆ generateAndSetAsimov()

void AsymptoticExclusion::generateAndSetAsimov ( double mu_prime )

This will trigger the XeRun associated to produce an Asimov dataset with the specified signal strenght mu_prime. The generated asimov is set as current data for the profile likelihood.

◆ getMu_hat()

double AsymptoticExclusion::getMu_hat ( )

returns signal strenght best fit, if the fit has not been runned returns -9999

◆ LikelihoodScan()

void AsymptoticExclusion::LikelihoodScan ( )

LOOP over values of mu within

◆ setAlternativeXAxisVal()

void AsymptoticExclusion::setAlternativeXAxisVal ( double x )

inline

Will plot the limits Graphs as a function of another variable. A 2D Histo will be also filled with the limit reported for mass VS additionalAxis that can be plotted as a COLZ

◆ setNscanPoints()

void AsymptoticExclusion::setNscanPoints ( int nPoints )

inline

Set the number of scan points for the limit compyutation, default is 100.

◆ setRealData()

void AsymptoticExclusion::setRealData ( )

Set DM data as current data for the profile likelihood.

◆ setToyDataset()

void AsymptoticExclusion::setToyDataset	(	double	seed,
		double	mu_prime
	)

This will trigger the XeRun associated to produce an a toy dataset of bkg + signal with the specified signal strenght mu_prime. The generated dataset is set as current data for the profile likelihood.

◆ unconditionalFit()

double AsymptoticExclusion::unconditionalFit ( )

returns the -2log(likelihood(mu,theta)) for the unconditional fit and saves mu_hat best fit to an internal variable retrivable with "getMu_hat()", it aslo store the outcome of the fit into "logD" member.

◆ writeToFile()

void AsymptoticExclusion::writeToFile ( TString prefix = "limit_" )

Write to file the histograms

The documentation for this class was generated from the following files:

SOURCE/src/AsymptoticExclusion.h
SOURCE/src/AsymptoticExclusion.cxx

Public Member Functions

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ compute_pval_s_plus_b()

◆ computeExpectedLimit()

◆ computeLimits()

◆ computeQTestStat()

◆ computeSensitivity()

◆ computeSensitivityHagar()

◆ computeSigmaAsimov()

◆ conditionalFit()

◆ generateAndSetAsimov()

◆ getMu_hat()

◆ LikelihoodScan()

◆ setAlternativeXAxisVal()

◆ setNscanPoints()

◆ setRealData()

◆ setToyDataset()

◆ unconditionalFit()

◆ writeToFile()