be.ac.ulg.montefiore.run.jahmm
Class OpdfInteger

java.lang.Object
  be.ac.ulg.montefiore.run.jahmm.OpdfInteger

All Implemented Interfaces:

Opdf<ObservationInteger>, java.io.Serializable, java.lang.Cloneable

public class OpdfInteger
extends java.lang.Object
implements Opdf<ObservationInteger>

This class represents a distribution of a finite number of positive integer observations.

See Also:

Serialized Form

Constructor Summary

OpdfInteger(double[] probabilities)
Builds a new probability distribution which operates on integer values.

OpdfInteger(int nbEntries)
Builds a new probability distribution which operates on integer values.

Method Summary

OpdfInteger	clone()
void	fit(java.util.Collection<? extends ObservationInteger> co) Fits this observation probability (distribution) function to a (non empty) set of observations.
void	fit(java.util.Collection<? extends ObservationInteger> co, double[] weights) Fits this observation probability (distribution) function to a weighted (non empty) set of observations.
void	fit(ObservationInteger... oa) Fits this observation probability (distribution) function to a (non empty) set of observations.
void	fit(ObservationInteger[] o, double[] weights) Fits this observation probability (distribution) function to a weighted (non empty) set of observations.
ObservationInteger	generate() Generates a (pseudo) random observation according to this distribution.
int	nbEntries() Returns how many integers are associated to probabilities by this distribution.
double	probability(ObservationInteger o) Returns the probability (density) of an observation given a distribution.
java.lang.String	toString()
java.lang.String	toString(java.text.NumberFormat numberFormat) Returns a String describing this distribution.

Methods inherited from class java.lang.Object

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

Constructor Detail

OpdfInteger

public OpdfInteger(int nbEntries)

Builds a new probability distribution which operates on integer values. The probabilities are initialized so that the distribution is uniformaly distributed.

Parameters:

nbEntries - The number of values to which to associate probabilities. Observations handled by this distribution have to be higher or equal than 0 and strictly smaller than nbEntries.

OpdfInteger

public OpdfInteger(double[] probabilities)

Builds a new probability distribution which operates on integer values.

Parameters:

probabilities - Array holding one probability for each possible argument value (i.e. such that probabilities[i] is the probability of the observation i.

Method Detail

nbEntries

public int nbEntries()

Returns how many integers are associated to probabilities by this distribution.

Returns:

The number of integers are associated to probabilities.

probability

public double probability(ObservationInteger o)

Description copied from interface: Opdf

Returns the probability (density) of an observation given a distribution.

Specified by:

probability in interface Opdf<ObservationInteger>

Parameters:

o - An observation.

Returns:

The probability (density, if o takes continuous values) of o for this function.

generate

public ObservationInteger generate()

Description copied from interface: Opdf

Generates a (pseudo) random observation according to this distribution.

Specified by:

generate in interface Opdf<ObservationInteger>

Returns:

An observation.

fit

public void fit(ObservationInteger... oa)

Description copied from interface: Opdf

Fits this observation probability (distribution) function to a (non empty) set of observations. The meaning to give to fits should be has the maximum likelihood if possible.

Specified by:

fit in interface Opdf<ObservationInteger>

Parameters:

oa - An array of observations compatible with this function.

fit

public void fit(java.util.Collection<? extends ObservationInteger> co)

Description copied from interface: Opdf

Fits this observation probability (distribution) function to a (non empty) set of observations. The meaning to give to fits should be has the maximum likelihood if possible.

Specified by:

fit in interface Opdf<ObservationInteger>

Parameters:

co - A set of observations compatible with this function.

fit

public void fit(ObservationInteger[] o,
                double[] weights)

Description copied from interface: Opdf

Fits this observation probability (distribution) function to a weighted (non empty) set of observations. Equations (53) and (54) of Rabiner's A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition explain how the weights can be used.

Specified by:

fit in interface Opdf<ObservationInteger>

Parameters:

o - An array of observations compatible with this factory.

weights - The weight associated to each observation (such that weight.length == o.length and the sum of all the elements equals 1).

fit

public void fit(java.util.Collection<? extends ObservationInteger> co,
                double[] weights)

Description copied from interface: Opdf

Fits this observation probability (distribution) function to a weighted (non empty) set of observations. Equations (53) and (54) of Rabiner's A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition explain how the weights can be used.

Specified by:

fit in interface Opdf<ObservationInteger>

Parameters:

co - A set of observations compatible with this factory.

weights - The weight associated to each observation (such that weight.length == o.length and the sum of all the elements equals 1).

clone

public OpdfInteger clone()

Specified by:

clone in interface Opdf<ObservationInteger>

Overrides:

clone in class java.lang.Object

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

toString

public java.lang.String toString(java.text.NumberFormat numberFormat)

Description copied from interface: Opdf

Returns a String describing this distribution.

Specified by:

toString in interface Opdf<ObservationInteger>

Parameters:

numberFormat - A formatter used to convert the numbers (e.g. probabilities) to strings.

Returns:

A String describing this distribution.