Overview  Package   Class  Use  Deprecated  Index
Home >> All >> riso >> [ distributions overview ]	PREV CLASS  NEXT CLASS
SUMMARY:  JAVADOC |  SOURCE |  DOWNLOAD | NESTED | FIELD | CONSTR | METHOD	DETAIL: FIELD | CONSTR | METHOD

---

riso.distributions
Class Beta  

java.lang.Object
  riso.distributions.AbstractDistribution
      riso.distributions.Beta

All Implemented Interfaces:

ConditionalDistribution, Distribution, java.io.Serializable

---

public class Beta

extends AbstractDistribution

An instance of this class represents a beta distribution.

---

Field Summary
double	p
double	q

 

Fields inherited from class riso.distributions.AbstractDistribution

associated_variable

 

Constructor Summary

Beta()           Default constructor for this class.

Beta(double p, double q)           Constructs a beta distribution with the specified parameters.

 

Method Summary
double	cdf(double x)           Compute the cumulative distribution function of this beta distribution.
double[]	effective_support(double epsilon)           Always returns the interval [0,1] -- this is the support of all beta distributions.
double	expected_value()           Returns the expected value of this distribution.
java.lang.String	format_string(java.lang.String leading_ws)           Formats a string representation of this distribution.
double	log_prior()           Computes the log of the prior probability of the parameters of this distribution, assuming some prior distribution has been established.
int	ndimensions()           Returns the number of dimensions in which this distribution lives.
double	p(double[] x)           Computes the density at the point x.
void	pretty_input(riso.general.SmarterTokenizer st)           Read an instance of this distribution from an input stream.
double[]	random()           Return an instance of a random variable from this distribution.
double	sqrt_variance()           Returns the square root of the variance of this distribution.
double	update(double[][] x, double[] responsibility, int niter_max, double stopping_criterion)           Use data to modify the parameters of the distribution.

 

Methods inherited from class riso.distributions.AbstractDistribution

clone, get_density, get_nstates, initial_mix, log_p, ndimensions_child, ndimensions_parent, p, parse_string, pretty_output, random, set_variable, toString

 

Methods inherited from class java.lang.Object

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

 

Field Detail

p

public double p

---

q

public double q

Constructor Detail

Beta

public Beta(double p,
            double q)

Constructs a beta distribution with the specified parameters.

---

Beta

public Beta()

Default constructor for this class. Sets parameters p and q to 1.

Method Detail

ndimensions

public int ndimensions()

Returns the number of dimensions in which this distribution lives. Always returns 1.

Specified by:

ndimensions in interface Distribution

Overrides:

ndimensions in class AbstractDistribution

---

p

public double p(double[] x)

Computes the density at the point x.

---

cdf

public double cdf(double x)

Compute the cumulative distribution function of this beta distribution.

Specified by:

cdf in interface Distribution

Overrides:

cdf in class AbstractDistribution

---

log_prior

public double log_prior()
                 throws java.lang.Exception

Computes the log of the prior probability of the parameters of this distribution, assuming some prior distribution has been established. This may not be meaningful for all distributions.

Specified by:

log_prior in interface Distribution

Overrides:

log_prior in class AbstractDistribution

---

random

public double[] random()
                throws java.lang.Exception

Return an instance of a random variable from this distribution. This method is not implemented.

Specified by:

random in interface Distribution

Overrides:

random in class AbstractDistribution

---

update

public double update(double[][] x,
                     double[] responsibility,
                     int niter_max,
                     double stopping_criterion)
              throws java.lang.Exception

Use data to modify the parameters of the distribution. This method is not implemented.

Specified by:

update in interface Distribution

Overrides:

update in class AbstractDistribution

---

expected_value

public double expected_value()

Returns the expected value of this distribution.

Specified by:

expected_value in interface Distribution

Overrides:

expected_value in class AbstractDistribution

---

sqrt_variance

public double sqrt_variance()

Returns the square root of the variance of this distribution. This is equal to the scale parameter times the square root of the shape parameter.

Specified by:

sqrt_variance in interface Distribution

Overrides:

sqrt_variance in class AbstractDistribution

---

effective_support

public double[] effective_support(double epsilon)
                           throws java.lang.Exception

Always returns the interval [0,1] -- this is the support of all beta distributions.

Specified by:

effective_support in interface Distribution

Overrides:

effective_support in class AbstractDistribution

---

format_string

public java.lang.String format_string(java.lang.String leading_ws)

Formats a string representation of this distribution. Since the representation is only one line of output, the argument leading_ws is ignored.

Specified by:

format_string in interface ConditionalDistribution

Overrides:

format_string in class AbstractDistribution

---

pretty_input

public void pretty_input(riso.general.SmarterTokenizer st)
                  throws java.io.IOException

Read an instance of this distribution from an input stream. This is intended for input from a human-readable source; this is different from object serialization.

Overrides:

pretty_input in class AbstractDistribution

---

Overview  Package   Class  Use  Deprecated  Index
Home >> All >> riso >> [ distributions overview ]	PREV CLASS  NEXT CLASS
SUMMARY:  JAVADOC |  SOURCE |  DOWNLOAD | NESTED | FIELD | CONSTR | METHOD	DETAIL: FIELD | CONSTR | METHOD

---