Package org.apache.commons.math.distribution

Class ChiSquaredDistributionImpl

    • 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.

      • 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.

      • getDomainLowerBound

        protected 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.
        Specified by:
        getDomainLowerBound in class AbstractContinuousDistribution
        Parameters:
        p - the desired probability for the critical value
        Returns:
        domain value lower bound, i.e. P(X < lower bound) < p

      • getDomainUpperBound

        protected 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.
        Specified by:
        getDomainUpperBound in class AbstractContinuousDistribution
        Parameters:
        p - the desired probability for the critical value
        Returns:
        domain value upper bound, i.e. P(X < upper bound) > p

      • 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

      • getSolverAbsoluteAccuracy

        protected double getSolverAbsoluteAccuracy()
        Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.
        Overrides:
        getSolverAbsoluteAccuracy in class AbstractContinuousDistribution
        Returns:
        the solver absolute accuracy
        Since:
        2.1

      • 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