jMEF.MixtureModel Class Reference

Inherits java::io::Serializable.

List of all members.

Public Member Functions

MixtureModel (int n)

Class constructor.

double density (Parameter x)

Computes the density value $ f(x) $ of a mixture model.

void normalizeWeights ()

Normalizes the weights of the mixture models $\alpha_i$ such as $\sum_{i=1}^n \alpha_i = 1$ .

String toString ()

Method toString.

MixtureModel getRandomSubMixtureModel (int m)

Creates a sub-mixture by randomly picking components in the instance.

MixtureModel clone ()

Creates and returns a copy of the instance.

int getDimension ()

Return the dimension of the parameters of the mixture model.

PVector[] drawRandomPoints (int m)

Draws points from the considered mixture model.

Static Public Member Functions

static void save (MixtureModel mm, String fileName)

Saves a mixture model in a specified output file.

static MixtureModel load (String fileName)

Loads a mixture model from an input file.

static double KLDMC (MixtureModel f, MixtureModel g, int n)

Estimates the Kullback-Leibler divergence using a Monte-Carlo method.

static double KLDMC (MixtureModel f, MixtureModel g, PVector[] points)

Estimates the Kullback-Leibler divergence using a Monte-Carlo method.

Public Attributes

ExponentialFamily EF

Exponential family of the mixture model.

int size

Number of components in the mixture model.

double[] weight

Array containing the weights of the mixture components.

Parameter[] param

Array containing the parameters of the mixture components.

Detailed Description

Author:: Vincent Garcia
Frank Nielsen

Version:: 1.0

License

See file LICENSE.txt

Description

A mixture model is a powerful framework commonly used to estimate the probability density function (PDF) of a random variable. Let us consider a mixture model $f$

of size

. The probability density function $f$

evaluated at $x \in R^d$ is given by

$f(x) = \sum_{i=1}^n \alpha_i f_i(x)$

where $\alpha_i \in [0,1]$ denotes the weight of the $i^{\textrm{th}}$ mixture component $f_i$ such as $\sum_{i=1}^n \alpha_i=1$ . The MixtureModel class provides a convenient way to create and manage mixture of exponential families.

Constructor & Destructor Documentation

jMEF.MixtureModel.MixtureModel ( int n )

Class constructor.

Parameters:

n

number of components in the mixture models.

Member Function Documentation

MixtureModel jMEF.MixtureModel.clone ( )

Creates and returns a copy of the instance.

Returns:: a clone of the instance

double jMEF.MixtureModel.density ( Parameter x )

Computes the density value $ f(x) $ of a mixture model.

Parameters:

x

a point

Returns:: value of the density

PVector [] jMEF.MixtureModel.drawRandomPoints ( int m )

Draws points from the considered mixture model.

Parameters:

m

number of points to draw

Returns:: a point

int jMEF.MixtureModel.getDimension ( )

Return the dimension of the parameters of the mixture model.

Returns:: parameters's dimension

MixtureModel jMEF.MixtureModel.getRandomSubMixtureModel ( int m )

Creates a sub-mixture by randomly picking components in the instance.

Parameters:

m

number of components in the the sub mixture

Returns:: a sub-mixture of the instance

static double jMEF.MixtureModel.KLDMC	(	MixtureModel	f,
		MixtureModel	g,
		PVector[]	points
	)			`[static]`

Estimates the Kullback-Leibler divergence using a Monte-Carlo method.

Parameters:

	f	mixture model
	g	mixture model
	points	points drawn from f

Returns:: $D_{\mathrm{KL}}(f\|g)$

static double jMEF.MixtureModel.KLDMC	(	MixtureModel	f,
		MixtureModel	g,
		int	n
	)			`[static]`

Estimates the Kullback-Leibler divergence using a Monte-Carlo method.

Parameters:

	f	mixture model
	g	mixture model
	n	number of points drawn from f

Returns:: $D_{\mathrm{KL}}(f\|g)$

static MixtureModel jMEF.MixtureModel.load ( String fileName ) [static]

Loads a mixture model from an input file.

Parameters:

fileName

file name where the mixture model is stored

Returns:: mixture model loaded from fileName

void jMEF.MixtureModel.normalizeWeights ( )

Normalizes the weights of the mixture models $\alpha_i$ such as $\sum_{i=1}^n \alpha_i = 1$ .

static void jMEF.MixtureModel.save	(	MixtureModel	mm,
		String	fileName
	)			`[static]`

Saves a mixture model in a specified output file.

Parameters:

	mm	mixture model to be saved
	fileName	file name where the mixture model has to be saved

String jMEF.MixtureModel.toString ( )

Method toString.

Returns:: string describing the mixture model

Member Data Documentation

ExponentialFamily jMEF.MixtureModel.EF

Exponential family of the mixture model.

Parameter [] jMEF.MixtureModel.param

Array containing the parameters of the mixture components.

int jMEF.MixtureModel.size

Number of components in the mixture model.

double [] jMEF.MixtureModel.weight

Array containing the weights of the mixture components.

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

MixtureModel.java


Public Member Functions
	MixtureModel (int n)
	Class constructor.
double	density (Parameter x)
	Computes the density value of a mixture model.
void	normalizeWeights ()
	Normalizes the weights of the mixture models $\alpha_i$ such as $\sum_{i=1}^n \alpha_i = 1$ .
String	toString ()
	Method toString.
MixtureModel	getRandomSubMixtureModel (int m)
	Creates a sub-mixture by randomly picking components in the instance.
MixtureModel	clone ()
	Creates and returns a copy of the instance.
int	getDimension ()
	Return the dimension of the parameters of the mixture model.
PVector[]	drawRandomPoints (int m)
	Draws points from the considered mixture model.
Static Public Member Functions
static void	save (MixtureModel mm, String fileName)
	Saves a mixture model in a specified output file.
static MixtureModel	load (String fileName)
	Loads a mixture model from an input file.
static double	KLDMC (MixtureModel f, MixtureModel g, int n)
	Estimates the Kullback-Leibler divergence using a Monte-Carlo method.
static double	KLDMC (MixtureModel f, MixtureModel g, PVector[] points)
	Estimates the Kullback-Leibler divergence using a Monte-Carlo method.
Public Attributes
ExponentialFamily	EF
	Exponential family of the mixture model.
int	size
	Number of components in the mixture model.
double[]	weight
	Array containing the weights of the mixture components.
Parameter[]	param
	Array containing the parameters of the mixture components.