STK::GammaBase< Derived > Class Template Reference

Base class for the gamma models. More...

#include <STK_GammaBase.h>

Inheritance diagram for STK::GammaBase< 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	shape (int k, int j) const
Real	scale (int k, int j) const
void	initializeModelImpl ()
	Initialize the parameters of the model.
Real	lnComponentProbability (int i, int k) const
template<class Weights >
Real	impute (int i, int j, Weights const &pk) const
Real	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 parameters in an array of size (2*nbCluster, nbVariable).
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
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
	GammaBase (int nbCluster)
	default constructor
	GammaBase (GammaBase const &model)
	copy constructor
	~GammaBase ()
	destructor
Real	qValue (CArrayXX const *p_tik, CPointX const *p_tk) const
	compute the Q(theta) value.
bool	moments (CArrayXX const *p_tik)
	compute the weighted moments of a gamma mixture.
Real	meanjk (int j, int k)
	get the weighted mean of the jth variable of the kth cluster.
Real	variancejk (int j, int k)
	get the weighted variance of the jth variable of the kth cluster.
Real	meank (int k)
	get the mean of the weighted means of the kth cluster.
Real	variancek (int k)
	get the mean of the weighted variances of the kth cluster.
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::GammaBase< Derived >

Base class for the gamma models.

Definition at line 95 of file STK_GammaBase.h.

Member Typedef Documentation

Base

template<class Derived >

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

Definition at line 98 of file STK_GammaBase.h.

Constructor & Destructor Documentation

GammaBase() [1/2]

template<class Derived >

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

inlineprotected

default constructor

Parameters

nbCluster

number of cluster in the model

Definition at line 106 of file STK_GammaBase.h.

: Base(nbCluster) {}

GammaBase() [2/2]

template<class Derived >

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

inlineprotected

copy constructor

Parameters

model

The model to copy

Definition at line 110 of file STK_GammaBase.h.

: Base(model) {}

~GammaBase()

template<class Derived >

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

inlineprotected

destructor

Definition at line 112 of file STK_GammaBase.h.

{}

Member Function Documentation

getParameters()

template<class Derived >

template<class Array >

void STK::GammaBase< Derived >::getParameters

(

Array &

params

)

const

This function is used in order to get the current values of the parameters in an array of size (2*nbCluster, nbVariable).

Parameters

[out]

params

the array with the parameters of the mixture.

Definition at line 259 of file STK_GammaBase.h.

{
  int nbClust = this->nbCluster();
  params.resize(2*nbClust, p_data()->cols());
  for (int k= 0; k < nbClust; ++k)
  {
    for (int j=  p_data()->beginCols();  j< p_data()->endCols(); ++j)
    {
      params(baseIdx+2*k  , j) = shape(baseIdx+k,j);
      params(baseIdx+2*k+1, j) = scale(baseIdx+k,j);
    }
  }
}

References STK::baseIdx.

impute()

template<class Derived >

template<class Weights >

Real STK::GammaBase< 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 186 of file STK_GammaBase.h.

{
  Real sum = 0.;
  for (int k= pk.begin(); k < pk.end(); ++k)
  { sum += pk[k] * shape(k,j) * scale(k,j);}
  return sum;
}

References STK::sum().

initializeModelImpl()

template<class Derived >

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

inline

Initialize the parameters of the model.

Definition at line 121 of file STK_GammaBase.h.

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

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

lnComponentProbability()

template<class Derived >

Real STK::GammaBase< 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 170 of file STK_GammaBase.h.

{
  Real sum =0.;
  for (int j=p_data()->beginCols(); j<p_data()->endCols(); ++j)
  {
    if (param_.shape(k,j) && param_.scale(k,j))
    { sum += Law::Gamma::lpdf(p_data()->elt(i,j), param_.shape(k,j), param_.scale(k,j));}
  }
  return sum;
}

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

meanjk()

template<class Derived >

Real STK::GammaBase< Derived >::meanjk ( int  j, int  k  )

inlineprotected

get the weighted mean of the jth variable of the kth cluster.

Definition at line 157 of file STK_GammaBase.h.

{ return param_.mean_[k][j];}

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

meank()

template<class Derived >

Real STK::GammaBase< Derived >::meank ( int  k )

inlineprotected

get the mean of the weighted means of the kth cluster.

Definition at line 161 of file STK_GammaBase.h.

{ return param_.mean_[k].mean();}

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

moments()

template<class Derived >

bool STK::GammaBase< Derived >::moments ( CArrayXX const *  p_tik )

protected

compute the weighted moments of a gamma mixture.

Definition at line 196 of file STK_GammaBase.h.

{
  for (int k= p_tik->beginCols(); k < p_tik->endCols(); ++k)
  {
    CVectorX tikColk(p_tik->col(k), true); // create a reference
    for (int j=p_data()->beginCols(); j<p_data()->endCols(); ++j)
    {
      // mean
      Real mean =  p_data()->col(j).wmean(tikColk);
      if ( (mean<=0) || isNA(mean) ) { return false;}
      param_.mean_[k][j] = mean;
      // mean log
      Real meanLog =  p_data()->col(j).log().wmean(tikColk);
      if (isNA(meanLog)) { return false;}
      param_.meanLog_[k][j] = meanLog;
      // variance
      Real variance =  p_data()->col(j).wvariance(mean, tikColk);
      if ((variance<=0)||isNA(variance)){ return false;}
      param_.variance_[k][j] = variance;
    }
  }
  return true;
}

References STK::ICArray< Derived >::col(), STK::isNA(), and STK::mean().

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::GammaBase< Derived >::initializeModelImpl().

qValue()

template<class Derived >

Real STK::GammaBase< Derived >::qValue ( CArrayXX const *  p_tik, CPointX const *  p_tk  ) const

protected

compute the Q(theta) value.

Definition at line 222 of file STK_GammaBase.h.

{
  Real value = 0.;
  for (int k= p_tik->beginCols(); k < p_tik->endCols(); ++k)
  {
    Real sumjk=0.0;
    for (int j=p_data()->beginCols(); j<p_data()->endCols(); ++j)
    {
      Real a = shape(k,j), b = scale(k,j);
      sumjk += a * (param_.meanLog_[k][j]-std::log(b))
             - param_.mean_[k][j]/b - STK::Funct::lgamma(a);
    }
    value += p_tk->elt(k) * sumjk;
  }
  return value;
}

References STK::Funct::lgamma().

rand()

template<class Derived >

Real STK::GammaBase< 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 137 of file STK_GammaBase.h.

    { return Law::Gamma::rand(shape(k,j), scale(k,j));}

References STK::Law::Gamma::rand(), STK::GammaBase< Derived >::scale(), and STK::GammaBase< Derived >::shape().

scale()

template<class Derived >

Real STK::GammaBase< Derived >::scale ( int  k, int  j  ) const

inline

Returns

the scale of the kth cluster and jth variable

Definition at line 118 of file STK_GammaBase.h.

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

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

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

shape()

template<class Derived >

Real STK::GammaBase< Derived >::shape ( int  k, int  j  ) const

inline

Returns

the shape of the kth cluster and jth variable

Definition at line 116 of file STK_GammaBase.h.

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

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

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

variancejk()

template<class Derived >

Real STK::GammaBase< Derived >::variancejk ( int  j, int  k  )

inlineprotected

get the weighted variance of the jth variable of the kth cluster.

Definition at line 159 of file STK_GammaBase.h.

{ return param_.variance_[k][j];}

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

variancek()

template<class Derived >

Real STK::GammaBase< Derived >::variancek ( int  k )

inlineprotected

get the mean of the weighted variances of the kth cluster.

Definition at line 163 of file STK_GammaBase.h.

{ return param_.variance_[k].mean();}

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

writeParameters()

template<class Derived >

void STK::GammaBase< 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 240 of file STK_GammaBase.h.

{
  CPointX a(p_data()->cols()), b(p_data()->cols());
  for (int k= p_tik->beginCols(); k < p_tik->endCols(); ++k)
  {
    // store shape and scale values in an array for a nice output
    for (int j=p_data()->beginCols();  j < p_data()->endCols(); ++j)
    {
      a[j] = shape(k,j);
      b[j] = scale(k,j);
    }
    os << _T("---> Component ") << k << _T("\n");
    os << _T("shape = ") << a;
    os << _T("scale = ") << b;
  }
}

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::GammaBase< Derived >::initializeModelImpl(), STK::GammaBase< Derived >::meanjk(), STK::GammaBase< Derived >::meank(), STK::GammaBase< Derived >::scale(), STK::GammaBase< Derived >::shape(), STK::GammaBase< Derived >::variancejk(), and STK::GammaBase< Derived >::variancek().

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

• STK_GammaBase.h