Interface ContinuousDistribution

    • Method Summary

      All Methods Instance Methods Abstract Methods Default Methods 
      Modifier and Type Method Description
      double getDensity​(double value)
      In probability theory, a probability density function (pdf), or density of a continuous random variable is a function that describes the relative likelihood for this random variable to occur at a given point.
      double getDistribution​(double value)
      In probability theory and statistics, the cumulative distribution function (CDF), or just distribution function, describes the probability that a real-valued random variable X with a given probability distribution will be found at a value less than or equal to x.
      default double getLowerConfidenceQuantile​(double confidence)  
      double getQuantile​(double probability)
      The quantile function, for any distribution, is defined for real variables between zero and one and is mathematically the inverse of the cumulative distribution function.
      default double getUpperConfidenceQuantile​(double confidence)  
    • Method Detail

      • getDensity

        double getDensity​(double value)
        In probability theory, a probability density function (pdf), or density of a continuous random variable is a function that describes the relative likelihood for this random variable to occur at a given point. The probability for the random variable to fall within a particular region is given by the integral of this variable's density over the region. The probability density function is nonnegative everywhere, and its integral over the entire space is equal to one. WikipediA
        Parameters:
        value - x
        Returns:
        P(x)
      • getDistribution

        double getDistribution​(double value)
        In probability theory and statistics, the cumulative distribution function (CDF), or just distribution function, describes the probability that a real-valued random variable X with a given probability distribution will be found at a value less than or equal to x. Intuitively, it is the "area so far" function of the probability distribution. Cumulative distribution functions are also used to specify the distribution of multivariate random variables. WikipediA
        Parameters:
        value - x
        Returns:
        P(≤x)
      • getLowerConfidenceQuantile

        default double getLowerConfidenceQuantile​(double confidence)
      • getQuantile

        double getQuantile​(double probability)
        The quantile function, for any distribution, is defined for real variables between zero and one and is mathematically the inverse of the cumulative distribution function. WikipediA The input probability absolutely has to be [0.0, 1.0], but values close to 0.0 and 1.0 may be problematic
        Parameters:
        probability - P(<=x)
        Returns:
        x
      • getUpperConfidenceQuantile

        default double getUpperConfidenceQuantile​(double confidence)