org.apache.commons.math.distribution
Class GammaDistributionImpl

java.lang.Object
  org.apache.commons.math.distribution.AbstractDistribution
      org.apache.commons.math.distribution.AbstractContinuousDistribution
          org.apache.commons.math.distribution.GammaDistributionImpl

All Implemented Interfaces:

Serializable, ContinuousDistribution, Distribution, GammaDistribution, HasDensity<Double>

public class GammaDistributionImpl
extends AbstractContinuousDistribution
implements GammaDistribution, Serializable

The default implementation of GammaDistribution.

See Also:

Serialized Form

Field Summary

static double

DEFAULT_INVERSE_ABSOLUTE_ACCURACY Default inverse cumulative probability accuracy

Constructor Summary

GammaDistributionImpl(double alpha, double beta)
Create a new gamma distribution with the given alpha and beta values.

GammaDistributionImpl(double alpha, double beta, double inverseCumAccuracy)
Create a new gamma distribution with the given alpha and beta values.

Method Summary

double	cumulativeProbability(double x) For this distribution, X, this method returns P(X < x).
double	density(double x) Returns the probability density for a particular point.
double	density(Double x) Deprecated.
double	getAlpha() Access the shape parameter, alpha
double	getBeta() Access the scale parameter, beta
double	getNumericalMean() Returns the mean.
double	getNumericalVariance() Returns the variance.
double	getSupportLowerBound() Returns the upper bound of the support for the distribution.
double	getSupportUpperBound() Returns the upper bound of the support for the distribution.
double	inverseCumulativeProbability(double p) For this distribution, X, this method returns the critical point x, such that P(X < x) = p.
void	setAlpha(double alpha) Deprecated. as of 2.1 (class will become immutable in 3.0)
void	setBeta(double newBeta) Deprecated. as of 2.1 (class will become immutable in 3.0)

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

reseedRandomGenerator, sample, sample

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

cumulativeProbability

Methods inherited from class java.lang.Object

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

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

cumulativeProbability

Field Detail

DEFAULT_INVERSE_ABSOLUTE_ACCURACY

public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY

Default inverse cumulative probability accuracy

Since:

2.1

See Also:

Constant Field Values

Constructor Detail

GammaDistributionImpl

public GammaDistributionImpl(double alpha,
                             double beta)

Create a new gamma distribution with the given alpha and beta values.

Parameters:

alpha - the shape parameter.

beta - the scale parameter.

GammaDistributionImpl

public GammaDistributionImpl(double alpha,
                             double beta,
                             double inverseCumAccuracy)

Create a new gamma distribution with the given alpha and beta values.

Parameters:

alpha - the shape parameter.

beta - the scale parameter.

inverseCumAccuracy - the maximum absolute error in inverse cumulative probability estimates (defaults to DEFAULT_INVERSE_ABSOLUTE_ACCURACY)

Since:

2.1

Method Detail

cumulativeProbability

public double cumulativeProbability(double x)
                             throws MathException

For this distribution, X, this method returns P(X < x). The implementation of this method is based on:

• Chi-Squared Distribution, equation (9).
• Casella, G., & Berger, R. (1990). Statistical Inference. Belmont, CA: Duxbury Press.

Specified by:

cumulativeProbability in interface Distribution

Parameters:

x - the value at which the CDF is evaluated.

Returns:

CDF for this distribution.

Throws:

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

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.

Returns 0 for p=0 and Double.POSITIVE_INFINITY for p=1.

Specified by:

inverseCumulativeProbability in interface ContinuousDistribution

Overrides:

inverseCumulativeProbability in class AbstractContinuousDistribution

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.

IllegalArgumentException - if p is not a valid probability.

setAlpha

@Deprecated
public void setAlpha(double alpha)

Deprecated. as of 2.1 (class will become immutable in 3.0)

Modify the shape parameter, alpha.

Specified by:

setAlpha in interface GammaDistribution

Parameters:

alpha - the new shape parameter.

Throws:

IllegalArgumentException - if alpha is not positive.

getAlpha

public double getAlpha()

Access the shape parameter, alpha

Specified by:

getAlpha in interface GammaDistribution

Returns:

alpha.

setBeta

@Deprecated
public void setBeta(double newBeta)

Deprecated. as of 2.1 (class will become immutable in 3.0)

Modify the scale parameter, beta.

Specified by:

setBeta in interface GammaDistribution

Parameters:

newBeta - the new scale parameter.

Throws:

IllegalArgumentException - if newBeta is not positive.

getBeta

public double getBeta()

Access the scale parameter, beta

Specified by:

getBeta in interface GammaDistribution

Returns:

beta.

density

public double density(double x)

Returns the probability density for a particular point.

Overrides:

density in class AbstractContinuousDistribution

Parameters:

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

Returns:

The pdf at point x.

density

@Deprecated
public double density(Double x)

Deprecated.

Return the probability density for a particular point.

Specified by:

density in interface GammaDistribution

Specified by:

density in interface HasDensity<Double>

Parameters:

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

Returns:

The pdf at point x.

getSupportLowerBound

public double getSupportLowerBound()

Returns the upper bound of the support for the distribution. The lower bound of the support is always 0, regardless of the parameters.

Returns:

lower bound of the support (always 0)

Since:

2.2

getSupportUpperBound

public double getSupportUpperBound()

Returns the upper bound of the support for the distribution. The upper bound of the support is always positive infinity, regardless of the parameters.

Returns:

upper bound of the support (always Double.POSITIVE_INFINITY)

Since:

2.2

getNumericalMean

public double getNumericalMean()

Returns the mean. For shape parameter alpha and scale parameter beta, the mean is alpha * beta

Returns:

the mean

Since:

2.2

getNumericalVariance

public double getNumericalVariance()

Returns the variance. For shape parameter alpha and scale parameter beta, the variance is alpha * beta^2

Returns:

the variance

Since:

2.2