Class NormalDistribution

  • All Implemented Interfaces:
    ProbabilityDistribution

    public class NormalDistribution
    extends Object
    implements ProbabilityDistribution
    The Normal distribution has its density a Gaussian function. The Normal distribution is probably the most important single distribution. By the central limit theorem, under certain conditions, the sum of a number of random variables with finite means and variances approaches a Normal distribution as the number of variables increases. Laplace proved that the Normal distribution occurs as a limiting distribution of arithmetic means of independent, identically distributed random variables with finite second moment.

    The R equivalent functions are dnorm, pnorm, qnorm, rnorm.

    See Also:
    • Constructor Summary

      Constructors 
      Constructor Description
      NormalDistribution()
      Construct an instance of the standard Normal distribution with mean 0 and standard deviation 1.
      NormalDistribution​(double mu, double sigma)
      Construct a Normal distribution with mean mu and standard deviation sigma.
    • Method Summary

      All Methods Instance Methods Concrete 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.