STK::PoissonBase< Derived > Class Template Reference

Base class for the Poisson models. More...

#include <STK_PoissonBase.h>

Inheritance diagram for STK::PoissonBase< Derived >:

Public Types
typedef IMixtureDensity< Derived >	Base
Public Types inherited from STK::IMixtureDensity< Derived >
typedef hidden::MixtureTraits< Derived >::Array	Array
typedef hidden::MixtureTraits< Derived >::Parameters	Parameters
typedef hidden::Traits< Array >::Type	Type

Public Member Functions
Real	lambda (int k, int j) const
void	initializeModelImpl ()
	Initialize the parameters of the model.
Real	lnComponentProbability (int i, int k) const
template<class Weights >
int	impute (int i, int j, Weights const &pk) const
Real	impute (int i, int j, CArrayXX const *p_tik) const
int	rand (int i, int j, int k) const
template<class Array >
void	getParameters (Array &params) const
	This function is used in order to get the current values of the lambdas.
void	writeParameters (CArrayXX const *p_tik, ostream &os) const
	This function can be used to write summary of parameters to the output stream.
Array const *const &	p_data () const
int	nbCluster () const
Public Member Functions inherited from STK::IMixtureDensity< Derived >
	~IMixtureDensity ()
	destructor
int	nbCluster () const
int	nbSample () const
Real	lnNbSample () const
Array const *const &	p_data () const
Parameters const &	param () const
void	setData (Array const &data)
	Set the data set.
void	setData (Array const &data, int nbRow, int nbCol, bool byRow=true)
	Set the data set and give dimensions.
bool	initializeStep ()
	This function will be called at the beginning of the estimation process once the model is created and data is set.
void	setParametersStep ()
	set the parameters obtained with the intermediate results and release the intermediate results.
void	finalizeStep ()
	This function will be called once the model is estimated.
template<class Weights >
Type	sample (int i, int j, Weights const &tk) const
Public Member Functions inherited from STK::IRecursiveTemplate< Derived >
Derived &	asDerived ()
	static cast : return a reference of this with a cast to the derived class.
Derived const &	asDerived () const
	static cast : return a const reference of this with a cast to the derived class.
Derived *	asPtrDerived ()
	static cast : return a ptr on a Derived of this with a cast to the derived class.
Derived const *	asPtrDerived () const
	static cast : return a ptr on a constant Derived of this with a cast to the derived class.
Derived *	clone () const
	create a leaf using the copy constructor of the Derived class.
Derived *	clone (bool isRef) const
	create a leaf using the copy constructor of the Derived class and a flag determining if the clone is a reference or not.

Public Attributes
Parameters	param_
	parameters of the derived mixture model.

Protected Member Functions
	PoissonBase (int nbCluster)
	default constructor
	PoissonBase (PoissonBase const &model)
	copy constructor
	~PoissonBase ()
	destructor
Protected Member Functions inherited from STK::IMixtureDensity< Derived >
	IMixtureDensity (int nbCluster)
	Default constructor.
	IMixtureDensity (IMixtureDensity const &model)
	copy constructor.
void	initializeModel ()
	Initialize the model before its first use.
bool	initializeStepImpl ()
	default implementation of initializeStepImpl (do nothing and return true)
void	finalizeStepImpl ()
	default implementation of finalizeStepImpl (do nothing)
void	setNbSample (int nbSample)
	Set the number of sample of the model (needed by kernel models)
Protected Member Functions inherited from STK::IRecursiveTemplate< Derived >
	IRecursiveTemplate ()
	constructor.
	~IRecursiveTemplate ()
	destructor.

Additional Inherited Members
Protected Attributes inherited from STK::IMixtureDensity< Derived >
Parameters	param_
	parameters of the derived mixture model.

Detailed Description

template<class Derived>
class STK::PoissonBase< Derived >

Base class for the Poisson models.

Definition at line 48 of file STK_PoissonBase.h.

Member Typedef Documentation

Base

template<class Derived >

typedef IMixtureDensity<Derived > STK::PoissonBase< Derived >::Base

Definition at line 51 of file STK_PoissonBase.h.

Constructor & Destructor Documentation

PoissonBase() [1/2]

template<class Derived >

STK::PoissonBase< Derived >::PoissonBase ( int  nbCluster )

inlineprotected

default constructor

Parameters

nbCluster

number of cluster in the model

Definition at line 60 of file STK_PoissonBase.h.

: Base(nbCluster) {}

PoissonBase() [2/2]

template<class Derived >

STK::PoissonBase< Derived >::PoissonBase ( PoissonBase< Derived > const &  model )

inlineprotected

copy constructor

Parameters

model

The model to copy

Definition at line 64 of file STK_PoissonBase.h.

: Base(model) {}

~PoissonBase()

template<class Derived >

STK::PoissonBase< Derived >::~PoissonBase ( )

inlineprotected

destructor

Definition at line 66 of file STK_PoissonBase.h.

{}

Member Function Documentation

getParameters()

template<class Derived >

template<class Array >

void STK::PoissonBase< Derived >::getParameters

(

Array &

params

)

const

This function is used in order to get the current values of the lambdas.

Parameters

[out]

params

the array with the parameters of the mixture.

Definition at line 144 of file STK_PoissonBase.h.

{
  params.resize(nbCluster(), p_data()->cols());
  for (int k= params.beginRows(); k < params.endRows(); ++k)
  {
    for (int j= p_data()->beginCols();  j < p_data()->endCols(); ++j)
    { params(k, j) = lambda(k,j);}
  }
}

impute() [1/2]

template<class Derived >

Real STK::PoissonBase< Derived >::impute	(	int	i,
		int	j,
		CArrayXX const *	p_tik
	)		const

Returns

a value to impute for the jth variable of the ith sample

Definition at line 131 of file STK_PoissonBase.h.

{
  Real sum = 0.;
  for (int k= p_tik->beginCols(); k < p_tik->endCols(); ++k)
  { sum += p_tik->elt(i,k) * lambda(k,j);}
  return sum;
}

References STK::sum().

impute() [2/2]

template<class Derived >

template<class Weights >

int STK::PoissonBase< Derived >::impute	(	int	i,
		int	j,
		Weights const &	pk
	)		const

Returns

an imputation value for the jth variable of the ith sample

Parameters

i,j	indexes of the data to impute
pk	the probabilities of each class for the ith individual

Definition at line 121 of file STK_PoissonBase.h.

{
  Real sum = 0.;
  for (int k= pk.begin(); k < pk.end(); ++k)
  { sum += pk[k] * lambda(k,j);}
  return std::floor(sum+0.5);
}

References STK::sum().

initializeModelImpl()

template<class Derived >

void STK::PoissonBase< Derived >::initializeModelImpl ( )

inline

Initialize the parameters of the model.

Definition at line 72 of file STK_PoissonBase.h.

{ param_.resize(p_data()->cols());}

References STK::PoissonBase< Derived >::p_data(), and STK::PoissonBase< Derived >::param_.

lambda()

template<class Derived >

Real STK::PoissonBase< Derived >::lambda ( int  k, int  j  ) const

inline

Returns

the value of lambda of the kth cluster and jth variable

Definition at line 70 of file STK_PoissonBase.h.

{ return param_.lambda(k,j);}

References STK::PoissonBase< Derived >::param_.

Referenced by STK::PoissonBase< Derived >::rand().

lnComponentProbability()

template<class Derived >

Real STK::PoissonBase< Derived >::lnComponentProbability	(	int	i,
		int	k
	)		const

Returns

the value of the probability of the i-th sample in the k-th component.

Parameters

i,k	indexes of the sample and of the component

Definition at line 107 of file STK_PoissonBase.h.

{
  Real sum =0.;
  for (int j=p_data()->beginCols(); j<p_data()->endCols(); ++j)
  {
    Real value = lambda(k,j);
    if (value)
    { sum += Law::Poisson::lpdf(p_data()->elt(i,j), value);}
  }
  return sum;
}

References STK::Law::Poisson::lpdf(), and STK::sum().

nbCluster()

template<class Derived >

int STK::IMixtureDensity< Derived >::nbCluster ( ) const

inline

Returns

the number of cluster

Definition at line 124 of file STK_IMixtureDensity.h.

{ return nbCluster_;}

p_data()

template<class Derived >

Array const *const & STK::IMixtureDensity< Derived >::p_data ( ) const

inline

Returns

a pointer on the current data set

Definition at line 131 of file STK_IMixtureDensity.h.

{ return p_dataij_;}

Referenced by STK::PoissonBase< Derived >::initializeModelImpl().

rand()

template<class Derived >

int STK::PoissonBase< Derived >::rand ( int  i, int  j, int  k  ) const

inline

Returns

a simulated value for the jth variable of the ith sample in the kth cluster.

Parameters

i,j,k

indexes of the data to simulate

Definition at line 89 of file STK_PoissonBase.h.

    { return Law::Poisson::rand(lambda(k,j));}

References STK::PoissonBase< Derived >::lambda(), and STK::Law::Poisson::rand().

writeParameters()

template<class Derived >

void STK::PoissonBase< Derived >::writeParameters	(	CArrayXX const *	p_tik,
		ostream &	os
	)		const

This function can be used to write summary of parameters to the output stream.

Parameters

p_tik	a constant pointer on the posterior probabilities
os	Stream where you want to write the summary of parameters.

Definition at line 160 of file STK_PoissonBase.h.

{
  CPointX params(p_data()->cols());
  for (int k= p_tik->beginCols(); k < p_tik->endCols(); ++k)
  {
    for (int j= p_data()->beginCols();  j < p_data()->endCols(); ++j)
    { params[j] = lambda(k,j);}
    os << _T("---> Component ") << k << _T("\n");
    os << _T("lambda = ") << params;
  }
}

References _T.

Member Data Documentation

param_

template<class Derived >

Parameters STK::IMixtureDensity< Derived >::param_

parameters of the derived mixture model.

Should be an instance of the STK::ModelParameters struct.

See also

STK::ModelParameters

Definition at line 180 of file STK_IMixtureDensity.h.

Referenced by STK::PoissonBase< Derived >::initializeModelImpl(), and STK::PoissonBase< Derived >::lambda().

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

• STK_PoissonBase.h