org.apache.commons.math.distribution

Class AbstractContinuousDistribution

java.lang.Object

org.apache.commons.math.distribution.AbstractDistribution

org.apache.commons.math.distribution.AbstractContinuousDistribution

All Implemented Interfaces:

java.io.Serializable, ContinuousDistribution, Distribution

Direct Known Subclasses:

BetaDistributionImpl, CauchyDistributionImpl, ChiSquaredDistributionImpl, ExponentialDistributionImpl, FDistributionImpl, GammaDistributionImpl, NormalDistributionImpl, TDistributionImpl, WeibullDistributionImpl

public abstract class AbstractContinuousDistribution
extends AbstractDistribution
implements ContinuousDistribution, java.io.Serializable

Base class for continuous distributions. Default implementations are provided for some of the methods that do not vary from distribution to distribution.

Version:

$Revision: 1073498 $ $Date: 2011-02-22 21:57:26 +0100 (mar. 22 févr. 2011) $

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected RandomDataImpl	randomData RandomData instance used to generate samples from the distribution
private static long	serialVersionUID Serializable version identifier
private double	solverAbsoluteAccuracy Solver absolute accuracy for inverse cumulative computation

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	AbstractContinuousDistribution() Default constructor.

Method Summary

Modifier and Type	Method and Description
double	density(double x) Return the probability density for a particular point.
protected abstract double	getDomainLowerBound(double p) Access the domain value lower bound, based on p, used to bracket a CDF root.
protected abstract double	getDomainUpperBound(double p) Access the domain value upper bound, based on p, used to bracket a CDF root.
protected abstract double	getInitialDomain(double p) Access the initial domain value, based on p, used to bracket a CDF root.
protected double	getSolverAbsoluteAccuracy() Returns the solver absolute accuracy for inverse cumulative computation.
double	inverseCumulativeProbability(double p) For this distribution, X, this method returns the critical point x, such that P(X < x) = p.
void	reseedRandomGenerator(long seed) Reseeds the random generator used to generate samples.
double	sample() Generates a random value sampled from this distribution.
double[]	sample(int sampleSize) Generates a random sample from the distribution.

Methods inherited from class org.apache.commons.math.distribution.AbstractDistribution

cumulativeProbability

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.apache.commons.math.distribution.Distribution

cumulativeProbability, cumulativeProbability

Field Detail

serialVersionUID

private static final long serialVersionUID

Serializable version identifier

See Also:

Constant Field Values

randomData

protected final RandomDataImpl randomData

RandomData instance used to generate samples from the distribution

Since:

2.2

solverAbsoluteAccuracy

private double solverAbsoluteAccuracy

Solver absolute accuracy for inverse cumulative computation

Since:

2.1

Constructor Detail

AbstractContinuousDistribution

protected AbstractContinuousDistribution()

Default constructor.

Method Detail

density

public double density(double x)
               throws MathRuntimeException

Return the probability density for a particular point.

Parameters:

x - The point at which the density should be computed.

Returns:

The pdf at point x.

Throws:

MathRuntimeException - if the specialized class hasn't implemented this function

Since:

2.1

inverseCumulativeProbability

public double inverseCumulativeProbability(double p)
                                    throws MathException

For this distribution, X, this method returns the critical point x, such that P(X < x) = p.

Specified by:

inverseCumulativeProbability in interface ContinuousDistribution

Parameters:

p - the desired probability

Returns:

x, such that P(X < x) = p

Throws:

MathException - if the inverse cumulative probability can not be computed due to convergence or other numerical errors.

java.lang.IllegalArgumentException - if p is not a valid probability.

reseedRandomGenerator

public void reseedRandomGenerator(long seed)

Reseeds the random generator used to generate samples.

Parameters:

seed - the new seed

Since:

2.2

sample

public double sample()
              throws MathException

Generates a random value sampled from this distribution. The default implementation uses the inversion method.

Returns:

random value

Throws:

MathException - if an error occurs generating the random value

Since:

2.2

sample

public double[] sample(int sampleSize)
                throws MathException

Generates a random sample from the distribution. The default implementation generates the sample by calling sample() in a loop.

Parameters:

sampleSize - number of random values to generate

Returns:

an array representing the random sample

Throws:

MathException - if an error occurs generating the sample

java.lang.IllegalArgumentException - if sampleSize is not positive

Since:

2.2

getInitialDomain

protected abstract double getInitialDomain(double p)

Access the initial domain value, based on p, used to bracket a CDF root. This method is used by inverseCumulativeProbability(double) to find critical values.

Parameters:

p - the desired probability for the critical value

Returns:

initial domain value

getDomainLowerBound

protected abstract double getDomainLowerBound(double p)

Access the domain value lower bound, based on p, used to bracket a CDF root. This method is used by inverseCumulativeProbability(double) to find critical values.

Parameters:

p - the desired probability for the critical value

Returns:

domain value lower bound, i.e. P(X < lower bound) < p

getDomainUpperBound

protected abstract double getDomainUpperBound(double p)

Access the domain value upper bound, based on p, used to bracket a CDF root. This method is used by inverseCumulativeProbability(double) to find critical values.

Parameters:

p - the desired probability for the critical value

Returns:

domain value upper bound, i.e. P(X < upper bound) > p

getSolverAbsoluteAccuracy

protected double getSolverAbsoluteAccuracy()

Returns the solver absolute accuracy for inverse cumulative computation.

Returns:

the maximum absolute error in inverse cumulative probability estimates

Since:

2.1