Package 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:
Serializable, ChiSquaredDistribution, ContinuousDistribution, Distribution, HasDensity<Double>
public class ChiSquaredDistributionImpl extends AbstractContinuousDistribution implements ChiSquaredDistribution, Serializable
The default implementation of ChiSquaredDistribution
See Also:

  • Field Details

    • DEFAULT_INVERSE_ABSOLUTE_ACCURACY

      public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY
      Default inverse cumulative probability accuracy
      Since:
      2.1
      See Also:

  • Constructor Details

    • 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 Details

    • 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(Double x)
      Deprecated.
      Return the probability density for a particular point.
      Specified by:
      density in interface ChiSquaredDistribution
      Specified by:
      density in interface HasDensity<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.
      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