A Bernoulli model, is a statistical model of the following form. More...

#include <STK_BernoulliModel.h>

Inheritance diagram for STK::BernoulliModel< Array, WColVector >:

Public Types
typedef Array::Type	Type
	Type of the data contained in the container.

typedef IUnivStatModel< Array, WColVector, Law::Bernoulli >	Base
	Base class.

Public Types inherited from STK::IUnivStatModel< Array, WColVector, Law::Bernoulli >
typedef ColVector::Type	Type
	Type of the data contained in the container.

typedef IRunnerUnsupervised< Array, WColVector >	Runner
	Type of the Runner.

Public Member Functions
	BernoulliModel ()
	default constructor.

	BernoulliModel (Array const &data)
	Constructor with data set.

	BernoulliModel (Array const *p_data)
	Constructor with a ptr on the data set.

	BernoulliModel (BernoulliModel const &model)
	Copy constructor.

BernoulliModel *	clone () const
	clone patern

virtual	~BernoulliModel ()
	destructor

virtual int	computeNbFreeParameters () const
	compute the number of free parameters

Public Member Functions inherited from STK::IUnivStatModel< Array, WColVector, Law::Bernoulli >
virtual	~IUnivStatModel ()
	destructor

Real	computeLnLikelihood () const
	compute the log Likelihood of the statistical model.

Law::Bernoulli const &	law () const

virtual bool	run ()
	Estimate the parameters of the model and update the.

virtual bool	run (WColVector const &weights)
	compute the weighted empirical probability of success based on the observed variables.

Public Member Functions inherited from STK::IStatModelBase
int	nbSample () const

Real	lnNbSample () const

int	nbVariable () const

Real	lnLikelihood () const

Real	likelihood () const

int	nbFreeParameter () const

Real	computeBIC () const

Real	computeAIC () const

Real	computeML () const

Public Member Functions inherited from STK::IRunnerUnsupervised< Array, Weights_ >
Array const *	p_data () const
	get the data set

virtual void	setData (Array const *p_data)
	Set the data set.

virtual void	setData (Array const &data)
	Set the data set.

virtual bool	run (Weights_ const &weights)=0
	run the weighted computations.

Public Member Functions inherited from STK::IRunnerBase
String const &	error () const
	get the last error message.

Protected Member Functions
virtual void	computeParameters ()
	compute the empirical probability of success based on the observed variables.

virtual void	computeParameters (WColVector const &weights)
	compute the weighted empirical probability of success based on the observed variables.

Protected Member Functions inherited from STK::IUnivStatModel< Array, WColVector, Law::Bernoulli >
	IUnivStatModel ()
	default constructor.

	IUnivStatModel (Array const &data)
	Constructor with data set.

	IUnivStatModel (Array const *p_data)
	Constructor with a ptr on the data set.

	IUnivStatModel (IUnivStatModel const &model)
	Copy constructor.

virtual void	update ()
	This virtual method will be called if the user set a new data set.

Protected Member Functions inherited from STK::IStatModelBase
	IStatModelBase ()
	Default constructor.

	IStatModelBase (int nbSample)
	Constructor with specified dimension.

	IStatModelBase (int nbSample, int nbVariable)
	Constructor with specified dimension.

	IStatModelBase (IStatModelBase const &model)
	Copy constructor.

	~IStatModelBase ()
	destructor

void	setNbFreeParameter (int const &nbFreeParameter)
	set the number of free parameters of the model

void	setNbSample (int const &nbSample)
	set the number of samples of the model

void	setNbVariable (int const &nbVariable)
	set the number of variables of the model

void	setLnLikelihood (Real const &lnLikelihood)
	set the log-likelihood of the model

void	initialize (int nbSample, int nbVariable)
	set the dimensions of the parameters of the model

Protected Member Functions inherited from STK::IRunnerUnsupervised< Array, Weights_ >
	IRunnerUnsupervised ()
	default constructor.

	IRunnerUnsupervised (Array const *const p_data)
	constructor with a pointer on the constant data set

	IRunnerUnsupervised (Array const &data)
	constructor with a constant reference on the data set

	IRunnerUnsupervised (IRunnerUnsupervised const &runner)
	copy constructor

	~IRunnerUnsupervised ()
	destructor

Protected Member Functions inherited from STK::IRunnerBase
	IRunnerBase ()
	default constructor

	IRunnerBase (IRunnerBase const &runner)
	copy constructor

virtual	~IRunnerBase ()
	destructor

Additional Inherited Members
Protected Attributes inherited from STK::IUnivStatModel< Array, WColVector, Law::Bernoulli >
Law::Bernoulli	law_
	The probability law of the model.

Protected Attributes inherited from STK::IRunnerUnsupervised< Array, Weights_ >
Array const *	p_data_
	A pointer on the original data set.

Protected Attributes inherited from STK::IRunnerBase
String	msg_error_
	String with the last error message.

bool	hasRun_
	`true` if run has been used, `false` otherwise

Detailed Description

template<class Array, class WColVector>
class STK::BernoulliModel< Array, WColVector >

A Bernoulli model, is a statistical model of the following form.

$f(x_i = x|\theta) = p^{x_i} (1-p)^{1-x_i}, \quad x_i\in\{0,1\}, \quad i=1\ldots,n.$

Definition at line 57 of file STK_BernoulliModel.h.

Member Typedef Documentation

◆ Base

template<class Array , class WColVector >

typedef IUnivStatModel<Array, WColVector, Law::Bernoulli> STK::BernoulliModel< Array, WColVector >::Base

Base class.

Definition at line 65 of file STK_BernoulliModel.h.

◆ Type

template<class Array , class WColVector >

typedef Array::Type STK::BernoulliModel< Array, WColVector >::Type

Type of the data contained in the container.

Definition at line 63 of file STK_BernoulliModel.h.

Constructor & Destructor Documentation

◆ BernoulliModel() [1/4]

template<class Array , class WColVector >

STK::BernoulliModel< Array, WColVector >::BernoulliModel ( )

inline

default constructor.

Definition at line 67 of file STK_BernoulliModel.h.

67: Base() {}

STK::BernoulliModel::Base

IUnivStatModel< Array, WColVector, Law::Bernoulli > Base

Base class.

Definition STK_BernoulliModel.h:65

Referenced by STK::BernoulliModel< Array, WColVector >::clone().

◆ BernoulliModel() [2/4]

template<class Array , class WColVector >

STK::BernoulliModel< Array, WColVector >::BernoulliModel ( Array const & data )

inline

Constructor with data set.

Definition at line 69 of file STK_BernoulliModel.h.

69: Base(data) {}

◆ BernoulliModel() [3/4]

template<class Array , class WColVector >

STK::BernoulliModel< Array, WColVector >::BernoulliModel ( Array const * p_data )

inline

Constructor with a ptr on the data set.

Definition at line 71 of file STK_BernoulliModel.h.

71: Base(p_data) {}

STK::IRunnerUnsupervised::p_data

Array const * p_data() const

get the data set

Definition STK_IRunner.h:216

◆ BernoulliModel() [4/4]

template<class Array , class WColVector >

STK::BernoulliModel< Array, WColVector >::BernoulliModel ( BernoulliModel< Array, WColVector > const & model )

inline

Copy constructor.

Definition at line 73 of file STK_BernoulliModel.h.

73: Base(model) {}

◆ ~BernoulliModel()

template<class Array , class WColVector >

virtual STK::BernoulliModel< Array, WColVector >::~BernoulliModel ( )

inlinevirtual

destructor

Definition at line 77 of file STK_BernoulliModel.h.

77{}

Member Function Documentation

◆ clone()

template<class Array , class WColVector >

BernoulliModel * STK::BernoulliModel< Array, WColVector >::clone ( ) const

inline

clone patern

Definition at line 75 of file STK_BernoulliModel.h.

75{ return new BernoulliModel(*this);}

STK::BernoulliModel::BernoulliModel

BernoulliModel()

default constructor.

Definition STK_BernoulliModel.h:67

References STK::BernoulliModel< Array, WColVector >::BernoulliModel().

◆ computeNbFreeParameters()

template<class Array , class WColVector >

virtual int STK::BernoulliModel< Array, WColVector >::computeNbFreeParameters ( ) const

inlinevirtual

compute the number of free parameters

Implements STK::IUnivStatModel< Array, WColVector, Law::Bernoulli >.

Definition at line 79 of file STK_BernoulliModel.h.

79{ return 1;}

◆ computeParameters() [1/2]

template<class Array , class WColVector >

virtual void STK::BernoulliModel< Array, WColVector >::computeParameters ( )

inlineprotectedvirtual

compute the empirical probability of success based on the observed variables.

The NA values are discarded.

Implements STK::IUnivStatModel< Array, WColVector, Law::Bernoulli >.

Definition at line 85 of file STK_BernoulliModel.h.

    {
        Real sum=0.;
        int nbObs=p_data()->size();
        for (int i=p_data()->begin(); i<=p_data()->lastIdx(); ++i)
        { (p_data()->elt(i) == binaryNA_) ? --nbObs : sum += p_data()->elt(i);}
        if (nbObs != 0) { this->law_.setProb(sum/nbObs);}
                  else  { this->law_.setProb(0.);}
    }

References STK::binaryNA_, STK::IUnivStatModel< Array, WColVector, Law::Bernoulli >::law_, STK::IRunnerUnsupervised< Array, Weights_ >::p_data(), STK::Law::Bernoulli::setProb(), and STK::sum().

◆ computeParameters() [2/2]

template<class Array , class WColVector >

virtual void STK::BernoulliModel< Array, WColVector >::computeParameters ( WColVector const & weights )

inlineprotectedvirtual

compute the weighted empirical probability of success based on the observed variables.

The NA values are discarded.

Implements STK::IUnivStatModel< Array, WColVector, Law::Bernoulli >.

Definition at line 97 of file STK_BernoulliModel.h.

    {
        Real sum=0.;
        int nbObs=p_data()->size();
        for (int i=p_data()->begin(); i<=p_data()->lastIdx(); ++i)
        { (p_data()->elt(i) == binaryNA_) ? --nbObs : sum += weights[i]*p_data()->elt(i);}
        if (nbObs != 0) { this->law_.setProb(sum/nbObs);}
                  else { this->law_.setProb(0.);}
    }

References STK::binaryNA_, STK::IUnivStatModel< Array, WColVector, Law::Bernoulli >::law_, STK::IRunnerUnsupervised< Array, Weights_ >::p_data(), STK::Law::Bernoulli::setProb(), and STK::sum().

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

STK_BernoulliModel.h

Public Types

Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ Base

◆ Type

Constructor & Destructor Documentation

◆ BernoulliModel() [1/4]

◆ BernoulliModel() [2/4]

◆ BernoulliModel() [3/4]

◆ BernoulliModel() [4/4]

◆ ~BernoulliModel()

Member Function Documentation

◆ clone()

◆ computeNbFreeParameters()

◆ computeParameters() [1/2]

◆ computeParameters() [2/2]