lio.probdistributions.contchain
Class MarginalProbabilityVector

java.lang.Object
  lio.probdistributions.contchain.ContinuousProbDistribution
      lio.probdistributions.contchain.MarginalProbabilityVector

All Implemented Interfaces:

LiODependentResource, LiOResource, ProbDistribution

public class MarginalProbabilityVector
extends ContinuousProbDistribution
implements LiODependentResource

This class represents the marginal probability distributions of a set of variables. It assumes a gaussian distribution for them.

Field Summary

(package private) double[]	lowerLimits Lower limist for the variables
(package private) double[]	upperLimits Upper limits for the variables

Fields inherited from class lio.probdistributions.contchain.ContinuousProbDistribution

data, size

Constructor Summary

MarginalProbabilityVector()

Method Summary

LiOResourceDefinition	getDefinition() Return a LiOResDescription object which holds the name and all parameters that describe the resource.
double[]	getMeans() Getter for property means.
void	getTaskInformation(LiOTask task) Allows passing information of the task to the resource.
double[]	getVariances() Getter for property variances.
void	learn(Individual[] individuals) Learns a probability distribution from a set of data
static void	main(java.lang.String[] args)
Individual[]	sample(int nIndividuals) Samples a population from the probability distribution.
void	setBounds(ContChainBounds bounds) Fixes the range of values for individuals and their size.

Methods inherited from class java.lang.Object

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

Field Detail

upperLimits

double[] upperLimits

Upper limits for the variables

lowerLimits

double[] lowerLimits

Lower limist for the variables

Constructor Detail

MarginalProbabilityVector

public MarginalProbabilityVector()

Method Detail

getTaskInformation

public void getTaskInformation(LiOTask task)

Description copied from interface: LiODependentResource

Allows passing information of the task to the resource.

Specified by:

getTaskInformation in interface LiODependentResource

Parameters:

task - Task.

setBounds

public void setBounds(ContChainBounds bounds)

Fixes the range of values for individuals and their size.

Parameters:

bounds - Object containing the description of the individuals.

learn

public void learn(Individual[] individuals)

Learns a probability distribution from a set of data

Specified by:

learn in interface ProbDistribution

Parameters:

individuals - Set of individiduals from which de distribution is estimated.

sample

public Individual[] sample(int nIndividuals)

Samples a population from the probability distribution. @ param nIndividuals number of samples that must be sampled.

Specified by:

sample in interface ProbDistribution

Returns:

a Population with the specified number of samples.

getDefinition

public LiOResourceDefinition getDefinition()

Description copied from interface: LiOResource

Return a LiOResDescription object which holds the name and all parameters that describe the resource.

Specified by:

getDefinition in interface LiOResource

Returns:

A definition of the resource.

main

public static void main(java.lang.String[] args)

getMeans

public double[] getMeans()

Getter for property means.

Returns:

Value of property means.

getVariances

public double[] getVariances()

Getter for property variances.

Returns:

Value of property variances.