org.apache.commons.math.distribution

Class ChiSquaredDistributionImpl

java.lang.Object

org.apache.commons.math.distribution.AbstractDistribution

org.apache.commons.math.distribution.AbstractContinuousDistribution

org.apache.commons.math.distribution.ChiSquaredDistributionImpl

All Implemented Interfaces:

java.io.Serializable, ChiSquaredDistribution, ContinuousDistribution, Distribution, HasDensity<java.lang.Double>

public class ChiSquaredDistributionImpl
extends AbstractContinuousDistribution
implements ChiSquaredDistribution, java.io.Serializable

The default implementation of ChiSquaredDistribution

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static double	DEFAULT_INVERSE_ABSOLUTE_ACCURACY Default inverse cumulative probability accuracy

Constructor Summary

Constructors

Constructor and Description
ChiSquaredDistributionImpl(double df) Create a Chi-Squared distribution with the given degrees of freedom.
ChiSquaredDistributionImpl(double df, double inverseCumAccuracy) Create a Chi-Squared distribution with the given degrees of freedom and inverse cumulative probability accuracy.
ChiSquaredDistributionImpl(double df, GammaDistribution g) Deprecated. as of 2.1 (to avoid possibly inconsistent state, the "GammaDistribution" will be instantiated internally)

Method Summary

Modifier and Type	Method and Description
double	cumulativeProbability(double x) For this distribution, X, this method returns P(X < x).
double	density(double x) Return the probability density for a particular point.
double	density(java.lang.Double x) Deprecated.
double	getDegreesOfFreedom() Access the degrees of freedom.
double	getNumericalMean() Returns the mean of the distribution.
double	getNumericalVariance() Returns the variance of the distribution.
double	getSupportLowerBound() Returns the lower bound of the support for the distribution.
double	getSupportUpperBound() Returns the upper bound for 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	setDegreesOfFreedom(double degreesOfFreedom) Deprecated. as of 2.1 (class will become immutable in 3.0)
void	setGamma(GammaDistribution g) 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

ChiSquaredDistributionImpl

public ChiSquaredDistributionImpl(double df)

Create a Chi-Squared distribution with the given degrees of freedom.

Parameters:

df - degrees of freedom.

ChiSquaredDistributionImpl

@Deprecated
public ChiSquaredDistributionImpl(double df,
                                              GammaDistribution g)

Deprecated. as of 2.1 (to avoid possibly inconsistent state, the "GammaDistribution" will be instantiated internally)

Create a Chi-Squared distribution with the given degrees of freedom.

Parameters:

df - degrees of freedom.

g - the underlying gamma distribution used to compute probabilities.

Since:

1.2

ChiSquaredDistributionImpl

public ChiSquaredDistributionImpl(double df,
                                  double inverseCumAccuracy)

Create a Chi-Squared distribution with the given degrees of freedom and inverse cumulative probability accuracy.

Parameters:

df - degrees of freedom.

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

Since:

2.1

Method Detail

setDegreesOfFreedom

@Deprecated
public void setDegreesOfFreedom(double degreesOfFreedom)

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

Modify the degrees of freedom.

Specified by:

setDegreesOfFreedom in interface ChiSquaredDistribution

Parameters:

degreesOfFreedom - the new degrees of freedom.

getDegreesOfFreedom

public double getDegreesOfFreedom()

Access the degrees of freedom.

Specified by:

getDegreesOfFreedom in interface ChiSquaredDistribution

Returns:

the degrees of freedom.

density

@Deprecated
public double density(java.lang.Double x)

Deprecated.

Return the probability density for a particular point.

Specified by:

density in interface ChiSquaredDistribution

Specified by:

density in interface HasDensity<java.lang.Double>

Parameters:

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

Returns:

The pdf at point x.

density

public double density(double x)

Return 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.

Since:

2.1

cumulativeProbability

public double cumulativeProbability(double x)
                             throws MathException

For this distribution, X, this method returns P(X < x).

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.

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

setGamma

@Deprecated
public void setGamma(GammaDistribution g)

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

Modify the underlying gamma distribution. The caller is responsible for insuring the gamma distribution has the proper parameter settings.

Parameters:

g - the new distribution.

Since:

1.2 made public

getSupportLowerBound

public double getSupportLowerBound()

Returns the lower bound of the support for the distribution. The lower bound of the support is always 0 no matter the degrees of freedom.

Returns:

lower bound of the support (always 0)

Since:

2.2

getSupportUpperBound

public double getSupportUpperBound()

Returns the upper bound for the support for the distribution. The upper bound of the support is always positive infinity no matter the degrees of freedom.

Returns:

upper bound of the support (always Double.POSITIVE_INFINITY)

Since:

2.2

getNumericalMean

public double getNumericalMean()

Returns the mean of the distribution. For k degrees of freedom, the mean is k

Returns:

the mean

Since:

2.2

getNumericalVariance

public double getNumericalVariance()

Returns the variance of the distribution. For k degrees of freedom, the variance is 2 * k

Returns:

the variance

Since:

2.2