Class TDistribution.Degree3

All Implemented Interfaces:
Comparable<RandomNumber>, DoubleSupplier, Supplier<Double>, BasicFunction, NullaryFunction<Double>, PrimitiveFunction.Nullary, ContinuousDistribution, Distribution, AccessScalar<Double>, ComparableNumber<RandomNumber>, NumberDefinition
Enclosing class:
TDistribution

static final class TDistribution.Degree3 extends TDistribution
  • Constructor Details

    • Degree3

      Degree3()
  • Method Details

    • getDensity

      public double getDensity(double value)
      Description copied from interface: ContinuousDistribution
      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
      Specified by:
      getDensity in interface ContinuousDistribution
      Overrides:
      getDensity in class TDistribution
      Parameters:
      value - x
      Returns:
      P(x)
    • getDistribution

      public double getDistribution(double value)
      Description copied from interface: ContinuousDistribution
      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
      Specified by:
      getDistribution in interface ContinuousDistribution
      Overrides:
      getDistribution in class TDistribution
      Parameters:
      value - x
      Returns:
      P(≤x)