edu.umd.cloud9.example.clustering

Class UnivariateGaussianMixtureModel

java.lang.Object

edu.umd.cloud9.example.clustering.UnivariateGaussianMixtureModel

public class UnivariateGaussianMixtureModel
extends Object

Field Summary

Fields

Modifier and Type	Field and Description
PVector[]	param
int[]	pos
int	size
double[]	weight

Constructor Summary

Constructors

Constructor and Description
UnivariateGaussianMixtureModel() Class constructor.
UnivariateGaussianMixtureModel(int n)

Method Summary

Methods

Modifier and Type	Method and Description
UnivariateGaussianMixtureModel	clone() Creates and returns a copy of the instance.
double	density(Point x) Computes the density value of this mixture value.
static double	densityOfGaussian(Point x, PVector param) Computes the density value \f$ f(x;\mu,\sigma^2) \f$.
static Point	drawRandomPointFromGaussian(PVector L) Draws a point from the considered distribution.
Point[]	drawRandomPoints(int m) Draws points from the considered mixture model.
int	getDimension() Return the dimension of the parameters of the mixture model.
void	normalizeWeights() Normalizes the weights of the mixture models \f$ \alpha_i \f$ such as \f$ \sum_{i=1}^n \alpha_i = 1 \f$.
void	setSize(int n)
String	toString() Method toString.

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

size

public int size

weight

public double[] weight

pos

public int[] pos

param

public PVector[] param

Constructor Detail

UnivariateGaussianMixtureModel

public UnivariateGaussianMixtureModel()

Class constructor.

UnivariateGaussianMixtureModel

public UnivariateGaussianMixtureModel(int n)

Method Detail

setSize

public void setSize(int n)

density

public double density(Point x)

Computes the density value of this mixture value.

Parameters:

x - a point

Returns:

density value of this mixture value

normalizeWeights

public void normalizeWeights()

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

toString

public String toString()

Method toString.

Overrides:

toString in class Object

Returns:

string describing the mixture model

clone

public UnivariateGaussianMixtureModel clone()

Creates and returns a copy of the instance.

Overrides:

clone in class Object

Returns:

a clone of the instance

getDimension

public int getDimension()

Return the dimension of the parameters of the mixture model.

Returns:

parameters's dimension

drawRandomPoints

public Point[] drawRandomPoints(int m)

Draws points from the considered mixture model.

Parameters:

m - number of points to draw

Returns:

a point

densityOfGaussian

public static double densityOfGaussian(Point x,
                       PVector param)

Computes the density value \f$ f(x;\mu,\sigma^2) \f$.

Parameters:

x - point

param - parameters (source, natural, or expectation)

Returns:

\f$ f(x;\mu,\sigma^2) = \frac{1}{ \sqrt{2\pi \sigma^2} } \exp \left( - \frac{(x-\mu)^2}{ 2 \sigma^2} \right) \f$

drawRandomPointFromGaussian

public static Point drawRandomPointFromGaussian(PVector L)

Draws a point from the considered distribution.

Parameters:

L - source parameters \f$ \mathbf{\Lambda} = ( \mu , \sigma^2 )\f$

Returns:

a point