BCModel Class Reference

#include <BCModel.h>

Inheritance diagram for BCModel:

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Collaboration diagram for BCModel:

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List of all members.

Detailed Description

The base class for all user-defined models.

Author:: Daniel Kollar
Kevin Kröninger

Version:: 1.0

Date:: 08.2008 This class represents a model. It contains a container of parameters, their prior distributions and the conditional probabilities given those parameters. The methods which implement the prior and conditional probabilities have to be overloaded by the user in the user defined model class which will inherit from this class.

Definition at line 47 of file BCModel.h.


Public Member Functions
Member functions (miscellaneous methods)

int	AddParameter (BCParameter *parameter)
int	AddParameter (const char *name, double lowerlimit, double upperlimit)
double	APrioriProbability (std::vector< double > parameters)
void	CalculateErrorBandXY (int nx, double xmin, double xmax, int ny, double ymin, double ymax, int niter)
BCH1D *	CalculatePValue (std::vector< double > par, bool flag_histogram=false)
int	CheckParameters (std::vector< double > parameters)
double	ConditionalProbabilityEntry (BCDataPoint *datapoint, std::vector< double > parameters)
virtual void	CorrelateDataPointValues (std::vector< double > &x)
void	CreateData (int ndatasets, std::vector< double > parameters)
void	CreateDataGrid (int ndatasets, std::vector< double > parameters, std::vector< bool > grid, std::vector< double > limits)
void	CreateDataGridROOT (int ndatasets, std::vector< double > parameters, std::vector< bool > grid, std::vector< double > limits)
virtual void	DefineParameters ()
BCH1D *	DoGoodnessOfFitTest (const char *filename, std::vector< double > parameters)
BCH1D *	DoGoodnessOfFitTest (const char *filename)
BCH1D *	DoGoodnessOfFitTest (int ndatasets)
BCH1D *	DoGoodnessOfFitTest (int ndatasets, std::vector< double > parameters)
BCH1D *	DoGoodnessOfFitTest (int ndatasets, std::vector< double > parameters, std::vector< bool > grid, std::vector< double > limits)
BCH1D *	DoGoodnessOfFitTestROOT (int ndatasets, std::vector< double > parameters, std::vector< bool > grid, std::vector< double > limits)
double	Eval (std::vector< double > parameters)
double	EvalSampling (std::vector< double > parameters)
void	FindMode ()
void	FixDataAxis (int index, bool fixed)
BCH2D *	GetMarginalized (const char name1, const char name2)
BCH2D *	GetMarginalized (BCParameter parameter1, BCParameter parameter2)
BCH1D *	GetMarginalized (const char *name)
BCH1D *	GetMarginalized (BCParameter *parameter)
double	GetPValue ()
double	GetPvalueFromChi2 (std::vector< double > par, int sigma_index)
BCH1D *	GoodnessOfFitTest (const char *filenname, std::vector< double > parameters)
BCH1D *	GoodnessOfFitTestROOT (int ndatasets, const char *filename, std::vector< double > parameters)
double	HessianMatrixElement (BCParameter parameter1, BCParameter parameter2, std::vector< double > point)
double	Likelihood (std::vector< double > parameter)
virtual double	LogAPrioriProbability (std::vector< double > parameters)
virtual double	LogConditionalProbabilityEntry (BCDataPoint *datapoint, std::vector< double > parameters)
double	LogEval (std::vector< double > parameters)
virtual double	LogLikelihood (std::vector< double > parameter)
virtual double	LogPoissonProbability (int nentries, std::vector< double > parameters)
double	LogProbability (std::vector< double > parameter)
double	LogProbabilityNN (std::vector< double > parameter)
int	MarginalizeAll ()
BCH2D *	MarginalizeProbability (const char name1, const char name2)
BCH2D *	MarginalizeProbability (BCParameter parameter1, BCParameter parameter2)
BCH1D *	MarginalizeProbability (const char *name)
BCH1D *	MarginalizeProbability (BCParameter *parameter)
double	Normalize ()
double	PoissonProbability (int nentries, std::vector< double > parameters)
int	PrintAllMarginalized (const char *file, int hdiv=1, int ndiv=1)
int	PrintAllMarginalized1D (const char *filebase)
int	PrintAllMarginalized2D (const char *filebase)
void	PrintHessianMatrix (std::vector< double > parameters)
void	PrintResults (const char *file)
void	PrintSummary ()
double	Probability (std::vector< double > parameter)
double	ProbabilityNN (std::vector< double > parameter)
int	ReadErrorBandFromFile (const char *file)
int	ReadMarginalizedFromFile (const char *file)
int	ReadMode (const char *file)
virtual double	SamplingFunction (std::vector< double > parameters)
void	WriteMode (const char *file)
Constructors and destructors

	BCModel (const char *name)
	BCModel ()
virtual	~BCModel ()
Member functions (get)

double	GetBestFitParameter (int index)
double	GetBestFitParameterMarginalized (int index)
std::vector< double >	GetBestFitParameters ()
std::vector< double >	GetBestFitParametersMarginalized ()
BCDataPoint *	GetDataPoint (int index)
BCDataPoint *	GetDataPointLowerBoundaries ()
double	GetDataPointLowerBoundary (int index)
BCDataPoint *	GetDataPointUpperBoundaries ()
double	GetDataPointUpperBoundary (int index)
BCDataSet *	GetDataSet ()
std::vector< double >	GetErrorBand (double level)
TGraph *	GetErrorBandGraph (double level1, double level2)
TH2D *	GetErrorBandXY ()
TGraph *	GetFitFunctionGraph (std::vector< double > parameters, double xmin, double xmax, int n=1000)
TGraph *	GetFitFunctionGraph ()
TGraph *	GetFitFunctionGraph (std::vector< double > parameters)
bool	GetFixedDataAxis (int index)
bool	GetFlagBoundaries ()
int	GetIndex ()
double	GetModelAPosterioriProbability ()
double	GetModelAPrioriProbability ()
std::string	GetName ()
int	GetNDataPoints ()
int	GetNDataPointsMaximum ()
int	GetNDataPointsMinimum ()
double	GetNormalization ()
int	GetNParameters ()
BCParameter *	GetParameter (const char *name)
BCParameter *	GetParameter (int index)
Member functions (set)

void	SetDataBoundaries (int index, double lowerboundary, double upperboundary, bool fixed=false)
void	SetDataSet (BCDataSet *dataset)
void	SetErrorBandContinuous (bool flag)
void	SetIndex (int index)
void	SetModelAPosterioriProbability (double probability)
void	SetModelAPrioriProbability (double probability)
void	SetName (const char *name)
void	SetNDataPointsMaximum (int maximum)
void	SetNDataPointsMinimum (int minimum)
void	SetNormalization (double norm)
void	SetSingleDataPoint (BCDataSet *dataset, int index)
void	SetSingleDataPoint (BCDataPoint *datapoint)
Protected Attributes
BCDataSet *	fDataSet
int	fIndex
bool	flag_ConditionalProbabilityEntry
double	fModelAPosteriori
double	fModelAPriori
std::string	fName
int	fNDataPointsMaximum
int	fNDataPointsMinimum
BCParameterSet *	fParameterSet
double	fPValue
Private Member Functions
int	CompareStrings (const char string1, const char string2)
BCDataPoint *	VectorToDataPoint (std::vector< double > data)
Private Attributes
double	fNormalization

Constructor & Destructor Documentation

BCModel::BCModel ( )

The default constructor.

Definition at line 51 of file BCModel.cxx.

BCModel::BCModel ( const char * name )

A constructor.

Parameters:

name

The name of the model

Definition at line 26 of file BCModel.cxx.

BCModel::~BCModel ( ) [virtual]

The default destructor.

Definition at line 74 of file BCModel.cxx.

Member Function Documentation

int BCModel::AddParameter ( BCParameter * parameter )

Adds a parameter to the model.

Parameters:

parameter

A model parameter

See also:: AddParameter(const char * name, double lowerlimit, double upperlimit);

Definition at line 433 of file BCModel.cxx.

int BCModel::AddParameter	(	const char *	name,
		double	lowerlimit,
		double	upperlimit
	)

Adds a parameter to the parameter set

Parameters:

	name	The name of the parameter
	lowerlimit	The lower limit of the parameter values
	upperlimit	The upper limit of the parameter values

See also:: AddParameter(BCParameter* parameter);

Definition at line 413 of file BCModel.cxx.

double BCModel::APrioriProbability ( std::vector< double > parameters ) [inline]

Returns the prior probability.

Parameters:

parameters

A set of parameter values

Returns:: The prior probability p(parameters)

See also:: GetPrior(std::vector <double> parameters)

Definition at line 354 of file BCModel.h.

void BCModel::CalculateErrorBandXY	(	int	nx,
		double	xmin,
		double	xmax,
		int	ny,
		double	ymin,
		double	ymax,
		int	niter
	)

Returns upper and lower value for a given point x on the error band param x A vector of x-values param ymin The minimum value param ymax The maximum value

Definition at line 566 of file BCModel.cxx.

BCH1D * BCModel::CalculatePValue	(	std::vector< double >	par,
		bool	flag_histogram = `false`
	)

Definition at line 2276 of file BCModel.cxx.

int BCModel::CheckParameters ( std::vector< double > parameters )

Checks if a set of parameters values is within the given range.

Parameters:

parameters

A set of parameter values

Returns:: Error code (0: OK, -1 length of parameters not correct, -2 values not within range)

Definition at line 682 of file BCModel.cxx.

int BCModel::CompareStrings	(	const char *	string1,
		const char *	string2
	)			`[private]`

Compares to strings

Definition at line 2684 of file BCModel.cxx.

double BCModel::ConditionalProbabilityEntry	(	BCDataPoint *	datapoint,
		std::vector< double >	parameters
	)			`[inline]`

Returns a conditional probability. Method needs to be overloaded by the user.

Parameters:

	datapoint	A data point
	parameters	A set of parameter values

Returns:: The conditional probability p(datapoint|parameters)

See also:: GetConditionalEntry(BCDataPoint* datapoint, std::vector <double> parameters)

Definition at line 422 of file BCModel.h.

void BCModel::CorrelateDataPointValues ( std::vector< double > & x ) [virtual]

Constrains a data point

Parameters:

x

A vector of double

Definition at line 2315 of file BCModel.cxx.

void BCModel::CreateData	(	int	ndatasets,
		std::vector< double >	parameters
	)

Creates data sets given a set of parameters.

Parameters:

	ndatasets	The number of data sets to be created
	parameters	A set of parameter values

Definition at line 1290 of file BCModel.cxx.

void BCModel::CreateDataGrid	(	int	ndatasets,
		std::vector< double >	parameters,
		std::vector< bool >	grid,
		std::vector< double >	limits
	)

Creates data sets in a grid given a set of parameters.

Parameters:

	ndatasets	The number of data sets to be created
	parameters	A set of parameter values
	grid	Boolean for random (false) or grid values (true)
	limits	Limits for each data value

Definition at line 1309 of file BCModel.cxx.

void BCModel::CreateDataGridROOT	(	int	ndatasets,
		std::vector< double >	parameters,
		std::vector< bool >	grid,
		std::vector< double >	limits
	)

Creates data sets in a grid given a set of parameters.

Parameters:

	ndatasets	The number of data sets to be created
	parameters	A set of parameter values
	grid	Boolean for random (false) or grid values (true)
	limits	Limits for each data value

Definition at line 1581 of file BCModel.cxx.

virtual void BCModel::DefineParameters ( ) [inline, virtual]

Defines the parameters of the model Method needs to be overloaded by the user.

Definition at line 345 of file BCModel.h.

BCH1D * BCModel::DoGoodnessOfFitTest	(	const char *	filename,
		std::vector< double >	parameters
	)

Definition at line 2234 of file BCModel.cxx.

BCH1D * BCModel::DoGoodnessOfFitTest ( const char * filename )

Definition at line 2251 of file BCModel.cxx.

BCH1D * BCModel::DoGoodnessOfFitTest ( int ndatasets )

Definition at line 2214 of file BCModel.cxx.

BCH1D * BCModel::DoGoodnessOfFitTest	(	int	ndatasets,
		std::vector< double >	parameters
	)

Definition at line 2185 of file BCModel.cxx.

BCH1D * BCModel::DoGoodnessOfFitTest	(	int	ndatasets,
		std::vector< double >	parameters,
		std::vector< bool >	grid,
		std::vector< double >	limits
	)

Do goodness-of-fit test. Creates data sets and performs a goodness-of-fit test.

Parameters:

	ndatasets	The number of data sets to be created
	parameters	A set of parameter values
	grid	Boolean for random (false) or grid values (true)
	limits	Limits for each data value

CreateDataGrid(int ndatasets, std::vector <double> parameters, std::vector <bool> grid, std::vector <double> limits)

GoodnessOfFitTest(const char * filenname, std::vector <double> parameters)

Definition at line 2127 of file BCModel.cxx.

BCH1D * BCModel::DoGoodnessOfFitTestROOT	(	int	ndatasets,
		std::vector< double >	parameters,
		std::vector< bool >	grid,
		std::vector< double >	limits
	)

Definition at line 2156 of file BCModel.cxx.

double BCModel::Eval ( std::vector< double > parameters ) [inline, virtual]

Overloaded function to evaluate integral.

Reimplemented from BCIntegrate.

Definition at line 474 of file BCModel.h.

double BCModel::EvalSampling ( std::vector< double > parameters ) [virtual]

Overloaded function to evaluate integral.

Reimplemented from BCIntegrate.

Definition at line 557 of file BCModel.cxx.

void BCModel::FindMode ( )

Does the mode finding

Definition at line 713 of file BCModel.cxx.

void BCModel::FixDataAxis	(	int	index,
		bool	fixed
	)

Definition at line 2381 of file BCModel.cxx.

double BCModel::GetBestFitParameter ( int index ) [inline]

Returns the value of a particular parameter (defined by index) at the global mode of the posterior pdf.

Parameters:

index

The index of the parameter.

Returns:: The best fit parameter.

Definition at line 191 of file BCModel.h.

double BCModel::GetBestFitParameterMarginalized ( int index ) [inline]

Returns the value of a particular parameter (defined by index) at the modes of the marginalized posterior pdfs.

Parameters:

index

The index of the parameter.

Returns:: The best fit parameter

Definition at line 208 of file BCModel.h.

std::vector<double> BCModel::GetBestFitParameters ( ) [inline]

Returns the set of values of the parameters at the global mode of the posterior pdf.

Returns:: The best fit parameters

Definition at line 199 of file BCModel.h.

std::vector<double> BCModel::GetBestFitParametersMarginalized ( ) [inline]

Returns the set of values of the parameters at the modes of the marginalized posterior pdfs.

Returns:: The best fit parameters.

Definition at line 216 of file BCModel.h.

BCDataPoint * BCModel::GetDataPoint ( int index )

Parameters:

index

The index of the data point.

Returns:: The data point in the current data set at index

Definition at line 111 of file BCModel.cxx.

BCDataPoint* BCModel::GetDataPointLowerBoundaries ( ) [inline]

Returns:: The lower boundaries of possible data values.

Definition at line 115 of file BCModel.h.

double BCModel::GetDataPointLowerBoundary ( int index ) [inline]

Parameters:

index

The index of the variable.

Returns:: The lower boundary of possible data values for a particular variable.

Definition at line 128 of file BCModel.h.

BCDataPoint* BCModel::GetDataPointUpperBoundaries ( ) [inline]

Returns:: The upper boundaries of possible data values.

Definition at line 121 of file BCModel.h.

double BCModel::GetDataPointUpperBoundary ( int index ) [inline]

Parameters:

index

The index of the variable.

Returns:: The upper boundary of possible data values for a particular variable.

Definition at line 135 of file BCModel.h.

BCDataSet* BCModel::GetDataSet ( ) [inline]

Returns:: The data set.

Definition at line 109 of file BCModel.h.

std::vector< double > BCModel::GetErrorBand ( double level )

Returns a vector of y-values at a certain probability level.

Parameters:

level

The level of probability

Returns:: The vector of y-values

Definition at line 166 of file BCModel.cxx.

TGraph * BCModel::GetErrorBandGraph	(	double	level1,
		double	level2
	)

Definition at line 202 of file BCModel.cxx.

TH2D* BCModel::GetErrorBandXY ( ) [inline]

Returns:: The 2-d histogram of the error band.

Definition at line 222 of file BCModel.h.

TGraph * BCModel::GetFitFunctionGraph	(	std::vector< double >	parameters,
		double	xmin,
		double	xmax,
		int	n = `1000`
	)

Definition at line 265 of file BCModel.cxx.

TGraph* BCModel::GetFitFunctionGraph ( ) [inline]

Definition at line 236 of file BCModel.h.

TGraph * BCModel::GetFitFunctionGraph ( std::vector< double > parameters )

Definition at line 231 of file BCModel.cxx.

bool BCModel::GetFixedDataAxis ( int index )

Definition at line 2403 of file BCModel.cxx.

bool BCModel::GetFlagBoundaries ( )

Definition at line 294 of file BCModel.cxx.

int BCModel::GetIndex ( ) [inline]

Returns:: The index of the model.

Definition at line 85 of file BCModel.h.

BCH2D* BCModel::GetMarginalized	(	const char *	name1,
		const char *	name2
	)			`[inline]`

Definition at line 574 of file BCModel.h.

BCH2D * BCModel::GetMarginalized	(	BCParameter *	parameter1,
		BCParameter *	parameter2
	)

If MarginalizeAll method was used, the individual marginalized distributions with respect to otwo parameters can be retrieved using this method.

Parameters:

	parameter1	First parameter
	parameter2	Second parameter

Returns:: 2D marginalized probability

Definition at line 1239 of file BCModel.cxx.

BCH1D* BCModel::GetMarginalized ( const char * name ) [inline]

Definition at line 562 of file BCModel.h.

BCH1D * BCModel::GetMarginalized ( BCParameter * parameter )

If MarginalizeAll method was used, the individual marginalized distributions with respect to one parameter can be retrieved using this method.

Parameters:

parameter

Model parameter

Returns:: 1D marginalized probability

Definition at line 955 of file BCModel.cxx.

double BCModel::GetModelAPosterioriProbability ( ) [inline]

Returns:: The a posteriori probability.

Definition at line 97 of file BCModel.h.

double BCModel::GetModelAPrioriProbability ( ) [inline]

Returns:: The a priori probability.

Definition at line 91 of file BCModel.h.

std::string BCModel::GetName ( ) [inline]

Returns:: The name of the model.

Definition at line 79 of file BCModel.h.

int BCModel::GetNDataPoints ( )

Returns:: The number of data points in the current data set.

Definition at line 92 of file BCModel.cxx.

int BCModel::GetNDataPointsMaximum ( ) [inline]

Returns:: The maximum number of data points.

Definition at line 164 of file BCModel.h.

int BCModel::GetNDataPointsMinimum ( ) [inline]

Returns:: The minimum number of data points.

Definition at line 158 of file BCModel.h.

double BCModel::GetNormalization ( ) [inline]

Returns:: The normalization of the likelihood.

Definition at line 103 of file BCModel.h.

int BCModel::GetNParameters ( ) [inline]

Returns:: The number of parameters of the model.

Definition at line 170 of file BCModel.h.

BCParameter * BCModel::GetParameter ( const char * name )

Parameters:

name

The name of the parameter in the parameter set.

Returns:: The parameter.

Definition at line 141 of file BCModel.cxx.

BCParameter * BCModel::GetParameter ( int index )

Parameters:

index

The index of the parameter in the parameter set.

Returns:: The parameter.

Definition at line 124 of file BCModel.cxx.

double BCModel::GetPValue ( ) [inline]

Definition at line 659 of file BCModel.h.

double BCModel::GetPvalueFromChi2	(	std::vector< double >	par,
		int	sigma_index
	)

Calculate p-value from Chi2 distribution for Gaussian problems

Parameters:

	par	Parameter set for the calculation of the likelihood
	sigma_index	Index of the sigma/uncertainty for the data points (for data in format "x y erry" the index would be 2)

Definition at line 2260 of file BCModel.cxx.

BCH1D * BCModel::GoodnessOfFitTest	(	const char *	filenname,
		std::vector< double >	parameters
	)

Goodness-of-fit test. Assuming a certain set of parameters this function reads data from a file (which was created under the assumption of the model and the same set of parameters) and calculates the frequency distribution of the probability p(data|parameters).

Parameters:

	filename	A file which contains a list of files with ensembles
	parameters	The parameter values for which the probability is calculated

Returns:: A frequency distribution of the conditional probability for the data sets given the parameters

Definition at line 1829 of file BCModel.cxx.

BCH1D * BCModel::GoodnessOfFitTestROOT	(	int	ndatasets,
		const char *	filename,
		std::vector< double >	parameters
	)

Definition at line 1978 of file BCModel.cxx.

double BCModel::HessianMatrixElement	(	BCParameter *	parameter1,
		BCParameter *	parameter2,
		std::vector< double >	point
	)

Calculates the matrix element of the Hessian matrix

Parameters:

	parameter1	The parameter for the first derivative
	parameter2	The parameter for the first derivative

Returns:: The matrix element of the Hessian matrix

Definition at line 2322 of file BCModel.cxx.

double BCModel::Likelihood ( std::vector< double > parameter ) [inline]

Returns the likelihood

Parameters:

parameters

A set of parameter values

Returns:: The likelihood

Definition at line 372 of file BCModel.h.

virtual double BCModel::LogAPrioriProbability ( std::vector< double > parameters ) [inline, virtual]

Returns natural logarithm of the prior probability. Method needs to be overloaded by the user.

Parameters:

parameters

A set of parameter values

Returns:: The prior probability p(parameters)

See also:: GetPrior(std::vector <double> parameters)

Reimplemented in BCModelTest.

Definition at line 364 of file BCModel.h.

virtual double BCModel::LogConditionalProbabilityEntry	(	BCDataPoint *	datapoint,
		std::vector< double >	parameters
	)			`[inline, virtual]`

Returns a natural logarithm of conditional probability. Method needs to be overloaded by the user.

Parameters:

	datapoint	A data point
	parameters	A set of parameter values

Returns:: The conditional probability p(datapoint|parameters)

See also:: GetConditionalEntry(BCDataPoint* datapoint, std::vector <double> parameters)

Definition at line 433 of file BCModel.h.

double BCModel::LogEval ( std::vector< double > parameters ) [virtual]

Overloaded function to evaluate integral.

Reimplemented from BCIntegrate.

Definition at line 548 of file BCModel.cxx.

double BCModel::LogLikelihood ( std::vector< double > parameter ) [virtual]

Calculates natural logarithm of the likelihood. Method needs to be overloaded by the user.

Parameters:

parameters

A set of parameter values

Returns:: Natural logarithm of the likelihood

Reimplemented in BCModelTest.

Definition at line 525 of file BCModel.cxx.

virtual double BCModel::LogPoissonProbability	(	int	nentries,
		std::vector< double >	parameters
	)			`[inline, virtual]`

Returns a probability for the data set container. Method to be overloaded by the user.

Parameters:

parameters

A set of parameter values

Returns:: The probability for the data set container

See also:: GetPoisson(std::vector <double> parameters)

Definition at line 452 of file BCModel.h.

double BCModel::LogProbability ( std::vector< double > parameter )

Returns natural logarithm of the a posteriori probability given a set of parameter values

Parameters:

parameters

A set of parameter values

Returns:: The a posteriori probability

Definition at line 507 of file BCModel.cxx.

double BCModel::LogProbabilityNN ( std::vector< double > parameter )

Returns the natural logarithm of likelihood times prior probability given a set of parameter values

Parameters:

parameters

A set of parameter values

Returns:: The likelihood times prior probability

Definition at line 490 of file BCModel.cxx.

int BCModel::MarginalizeAll ( )

Marginalize all probabilities wrt. single parameters and all combinations of two parameters. The individual distributions can be retrieved using the GetMarginalized method.

Returns:: Total number of marginalized distributions

Definition at line 908 of file BCModel.cxx.

BCH2D* BCModel::MarginalizeProbability	(	const char *	name1,
		const char *	name2
	)			`[inline]`

Definition at line 543 of file BCModel.h.

BCH2D * BCModel::MarginalizeProbability	(	BCParameter *	parameter1,
		BCParameter *	parameter2
	)

Marginalizes the a posteriori probability with respect to two parameters.

Parameters:

	parameter1	First parameter
	parameter2	Second parameter

Returns:: 2D marginalized probability

Definition at line 880 of file BCModel.cxx.

BCH1D* BCModel::MarginalizeProbability ( const char * name ) [inline]

Definition at line 532 of file BCModel.h.

BCH1D * BCModel::MarginalizeProbability ( BCParameter * parameter )

Marginalizes the a posteriori probability with respect to a parameter.

Parameters:

parameter

A model parameter

Returns:: 1D marginalized probability

Definition at line 839 of file BCModel.cxx.

double BCModel::Normalize ( )

Integrates over the un-normalized probability and updates fNormalization.

Definition at line 655 of file BCModel.cxx.

double BCModel::PoissonProbability	(	int	nentries,
		std::vector< double >	parameters
	)			`[inline]`

Returns a probability for the data set container.

Parameters:

parameters

A set of parameter values

Returns:: The probability for the data set container

See also:: GetPoisson(std::vector <double> parameters)

Definition at line 442 of file BCModel.h.

int BCModel::PrintAllMarginalized	(	const char *	file,
		int	hdiv = `1`,
		int	ndiv = `1`
	)

Definition at line 1136 of file BCModel.cxx.

int BCModel::PrintAllMarginalized1D ( const char * filebase )

Definition at line 1088 of file BCModel.cxx.

int BCModel::PrintAllMarginalized2D ( const char * filebase )

Definition at line 1109 of file BCModel.cxx.

void BCModel::PrintHessianMatrix ( std::vector< double > parameters )

Prints matrix elements of the Hessian matrix

Parameters:

parameters

The parameter values at which point to evaluate the matrix

Definition at line 2633 of file BCModel.cxx.

void BCModel::PrintResults ( const char * file )

Prints a summary of the Markov Chain Monte Carlo to a file.

Definition at line 2488 of file BCModel.cxx.

void BCModel::PrintSummary ( )

Prints a summary on the screen.

Definition at line 2422 of file BCModel.cxx.

double BCModel::Probability ( std::vector< double > parameter ) [inline]

Returns the a posteriori probability given a set of parameter values

Parameters:

parameters

A set of parameter values

Returns:: The a posteriori probability

Definition at line 404 of file BCModel.h.

double BCModel::ProbabilityNN ( std::vector< double > parameter ) [inline]

Returns the likelihood times prior probability given a set of parameter values

Parameters:

parameters

A set of parameter values

Returns:: The likelihood times prior probability

Definition at line 388 of file BCModel.h.

int BCModel::ReadErrorBandFromFile ( const char * file )

Read

Definition at line 1058 of file BCModel.cxx.

int BCModel::ReadMarginalizedFromFile ( const char * file )

Read

Definition at line 1003 of file BCModel.cxx.

int BCModel::ReadMode ( const char * file )

Read mode from file created by WriteMode() call

Definition at line 796 of file BCModel.cxx.

double BCModel::SamplingFunction ( std::vector< double > parameters ) [virtual]

Sampling function used for importance sampling. Method needs to be overloaded by the user.

Parameters:

parameters

A set of parameter values

Returns:: The probability density at the parameter values

Definition at line 638 of file BCModel.cxx.

void BCModel::SetDataBoundaries	(	int	index,
		double	lowerboundary,
		double	upperboundary,
		bool	fixed = `false`
	)

Definition at line 346 of file BCModel.cxx.

void BCModel::SetDataSet ( BCDataSet * dataset ) [inline]

Sets the data set.

Parameters:

dataset

A data set

Definition at line 290 of file BCModel.h.

void BCModel::SetErrorBandContinuous ( bool flag )

Sets the error band flag to continuous function

Definition at line 390 of file BCModel.cxx.

void BCModel::SetIndex ( int index ) [inline]

Sets the index of the model within the BCModelManager.

Parameters:

index

The index of the model

Definition at line 259 of file BCModel.h.

void BCModel::SetModelAPosterioriProbability ( double probability ) [inline]

Sets the a posteriori probability for a model.

Parameters:

	model	The model
	probability	The a posteriori probability

Definition at line 275 of file BCModel.h.

void BCModel::SetModelAPrioriProbability ( double probability ) [inline]

Sets the a priori probability for a model.

Parameters:

	model	The model
	probability	The a priori probability

Definition at line 267 of file BCModel.h.

void BCModel::SetName ( const char * name ) [inline]

Sets the name of the model.

Parameters:

name

Name of the model

Definition at line 252 of file BCModel.h.

void BCModel::SetNDataPointsMaximum ( int maximum ) [inline]

Sets the maximum number of data points.

Definition at line 310 of file BCModel.h.

void BCModel::SetNDataPointsMinimum ( int minimum ) [inline]

Sets the minimum number of data points.

Definition at line 304 of file BCModel.h.

void BCModel::SetNormalization ( double norm ) [inline]

Sets the normalization of the likelihood. The normalization is the integral of likelihood over all parameters.

Parameters:

norm

The normalization of the likelihood

Definition at line 283 of file BCModel.h.

void BCModel::SetSingleDataPoint	(	BCDataSet *	dataset,
		int	index
	)

Definition at line 334 of file BCModel.cxx.

void BCModel::SetSingleDataPoint ( BCDataPoint * datapoint )

Sets a single data point as data set.

Parameters:

datapoint

A data point

Definition at line 315 of file BCModel.cxx.

BCDataPoint * BCModel::VectorToDataPoint ( std::vector< double > data ) [private]

Converts a vector of doubles into a BCDataPoint

Definition at line 2669 of file BCModel.cxx.

void BCModel::WriteMode ( const char * file )

Write mode into file

Definition at line 755 of file BCModel.cxx.

Member Data Documentation

BCDataSet* BCModel::fDataSet [protected]

A data set

Definition at line 720 of file BCModel.h.

int BCModel::fIndex [protected]

Index of the model.

Definition at line 695 of file BCModel.h.

bool BCModel::flag_ConditionalProbabilityEntry [protected]

Definition at line 735 of file BCModel.h.

double BCModel::fModelAPosteriori [protected]

The model a posteriori probability.

Definition at line 710 of file BCModel.h.

double BCModel::fModelAPriori [protected]

The model prior probability.

Definition at line 705 of file BCModel.h.

std::string BCModel::fName [protected]

Name of the model.

Definition at line 700 of file BCModel.h.

int BCModel::fNDataPointsMaximum [protected]

Maximum number of data points

Definition at line 730 of file BCModel.h.

int BCModel::fNDataPointsMinimum [protected]

Minimum number of data points

Definition at line 725 of file BCModel.h.

double BCModel::fNormalization [private]

The Likelihood normalization.

Definition at line 757 of file BCModel.h.

BCParameterSet* BCModel::fParameterSet [protected]

A model parameter container.

Definition at line 715 of file BCModel.h.

double BCModel::fPValue [protected]

The p-value

Definition at line 740 of file BCModel.h.

BCModel Class Reference

Detailed Description

Public Member Functions

Protected Attributes

Private Member Functions

Private Attributes

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation