Module ojalgo
Package org.ojalgo.random

Interface ContinuousDistribution

All Superinterfaces:
Distribution
All Known Implementing Classes:
AbstractContinuous, Cauchy, ChiSquareDistribution, ChiSquareDistribution.Degree2, ChiSquareDistribution.NormalApproximation, Exponential, LogNormal, Normal, TDistribution, TDistribution.Degree1, TDistribution.Degree2, TDistribution.Degree3, TDistribution.Degree4, TDistribution.Degree5, TDistribution.DegreeInfinity, Uniform
public interface ContinuousDistribution extends Distribution

  • Method Summary

    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)
     

    Methods inherited from interface org.ojalgo.random.Distribution

    getExpected, getStandardDeviation, getVariance

  • Method Details

    • 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)