Interface ProbabilityDistribution

    • Method Summary

      All Methods Instance Methods Abstract Methods 
      Modifier and Type Method Description
      double cdf​(double x)
      Gets the cumulative probability F(x) = Pr(X ≤ x).
      double density​(double x)
      The density function, which, if exists, is the derivative of F.
      double entropy()
      Gets the entropy of this distribution.
      double kurtosis()
      Gets the excess kurtosis of this distribution.
      double mean()
      Gets the mean of this distribution.
      double median()
      Gets the median of this distribution.
      double moment​(double t)
      The moment generating function is the expected value of etX.
      double quantile​(double u)
      Gets the quantile, the inverse of the cumulative distribution function.
      double skew()
      Gets the skewness of this distribution.
      double variance()
      Gets the variance of this distribution.
    • Method Detail

      • median

        double median()
        Gets the median of this distribution.
        Returns:
        the median
        See Also:
        Wikipedia: Median
      • variance

        double variance()
        Gets the variance of this distribution.
        Returns:
        the variance
        See Also:
        Wikipedia: Variance
      • skew

        double skew()
        Gets the skewness of this distribution.
        Returns:
        the skewness
        See Also:
        Wikipedia: Skewness
      • kurtosis

        double kurtosis()
        Gets the excess kurtosis of this distribution.
        Returns:
        the excess kurtosis
        See Also:
        Wikipedia: Kurtosis
      • quantile

        double quantile​(double u)
        Gets the quantile, the inverse of the cumulative distribution function. It is the value below which random draws from the distribution would fall u×100 percent of the time.
        
         F-1(u) = x, such that
         Pr(X ≤ x) = u
         
        This may not always exist.
        Parameters:
        u - u, a quantile
        Returns:
        F-1(u)
        See Also:
        Wikipedia: Quantile function
      • density

        double density​(double x)
        The density function, which, if exists, is the derivative of F. It describes the density of probability at each point in the sample space.
        f(x) = dF(X) / dx
        This may not always exist.

        For the discrete cases, this is the probability mass function. It gives the probability that a discrete random variable is exactly equal to some value.

        Parameters:
        x - x
        Returns:
        f(x)
        See Also:
      • moment

        double moment​(double t)
        The moment generating function is the expected value of etX. That is,
        E(etX)
        This may not always exist.
        Parameters:
        t - t
        Returns:
        E(exp(tX))
        See Also:
        Wikipedia: Moment-generating function