Package org.apache.commons.math.distribution

Class TDistributionImpl

    • 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

      • TDistributionImpl

        public TDistributionImpl​(double degreesOfFreedom,
                         double inverseCumAccuracy)
        Create a t distribution using the given degrees of freedom and the specified inverse cumulative probability absolute accuracy.
        Parameters:
        degreesOfFreedom - the degrees of freedom.
        inverseCumAccuracy - the maximum absolute error in inverse cumulative probability estimates (defaults to DEFAULT_INVERSE_ABSOLUTE_ACCURACY)
        Since:
        2.1

      • TDistributionImpl

        public TDistributionImpl​(double degreesOfFreedom)
        Create a t distribution using the given degrees of freedom.
        Parameters:
        degreesOfFreedom - the degrees of freedom.

    • 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 TDistribution
        Parameters:
        degreesOfFreedom - the new degrees of freedom.

      • getDegreesOfFreedom

        public double getDegreesOfFreedom()
        Access the degrees of freedom.
        Specified by:
        getDegreesOfFreedom in interface TDistribution
        Returns:
        the degrees of freedom.

      • 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.
        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 evaluated at x.
        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 Double.NEGATIVE_INFINITY 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

      • 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 negative infinity no matter the parameters.
        Returns:
        lower bound of the support (always Double.NEGATIVE_INFINITY)
        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 no matter the parameters.
        Returns:
        upper bound of the support (always Double.POSITIVE_INFINITY)
        Since:
        2.2

      • getNumericalMean

        public double getNumericalMean()
        Returns the mean. For degrees of freedom parameter df, the mean is
        • if df > 1 then 0
        • else undefined
        Returns:
        the mean
        Since:
        2.2

      • getNumericalVariance

        public double getNumericalVariance()
        Returns the variance. For degrees of freedom parameter df, the variance is
        • if df > 2 then df / (df - 2)
        • if 1 < df <= 2 then positive infinity
        • else undefined
        Returns:
        the variance
        Since:
        2.2