org.apache.commons.math.distribution

## Class ChiSquaredDistributionImpl

• ### 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

All Methods
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
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,
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:
• #### 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