| Name | Description |
|---|---|
| Beta | Implements the Beta distribution. For details about this distribution, see Wikipedia - Beta distribution. |
| Cauchy | The Cauchy distribution is a symmetric continuous probability distribution. For details about this distribution, see Wikipedia - Cauchy distribution. |
| Chi | This class implements functionality for the Chi distribution. This distribution is a continuous probability distribution. The distribution usually arises when a k-dimensional vector's orthogonal components are independent and each follow a standard normal distribution. The length of the vector will then have a chi distribution. Wikipedia - Chi distribution. |
| ChiSquare | This class implements functionality for the ChiSquare distribution. This distribution is a sum of the squares of k independent standard normal random variables. Wikipedia - ChiSquare distribution. |
| ContinuousUniform | 균일 연속 분포 The continuous uniform distribution is a distribution over real numbers. For details about this distribution, see Wikipedia - Continuous uniform distribution. |
| Erlang | Erlang 연속 분포 This class implements functionality for the Erlang distribution. This distribution is a continuous probability distribution with wide applicability primarily due to its relation to the exponential and Gamma distributions. Wikipedia - Erlang distribution. |
| Exponential | 지수 분포 The exponential distribution is a distribution over the real numbers parameterized by one non-negative parameter. Wikipedia - exponential distribution. |
| FisherSnedecor | Implements the FisherSnedecor distribution. For details about this distribution, see Wikipedia - FisherSnedecor distribution. |
| Gamma | Implements the univariate Gamma distribution. For details about this distribution, see Wikipedia - Gamma distribution. |
| InverseGamma | The inverse Gamma distribution is a distribution over the positive real numbers parameterized by two positive parameters. Wikipedia - InverseGamma distribution. |
| Laplace | The Laplace distribution is a distribution over the real numbers parameterized by a mean and scale parameter. The PDF is: p(x) = \frac{1}{2 * scale} \exp{- |x - mean| / scale}. Wikipedia - Laplace distribution. |
| Normal | 정규 분포. Implements the univariate Normal (or Gaussian) distribution. For details about this distribution, see Wikipedia - Normal distribution. |
| NormalFixture | |
| Pareto | The Pareto distribution is a power law probability distribution that coincides with social, scientific, geophysical, actuarial, and many other types of observable phenomena. For details about this distribution, see Wikipedia - Pareto distribution. |
| Rayleigh | The Rayleigh distribution (pronounced /ˈreɪli/) is a continuous probability distribution. As an example of how it arises, the wind speed will have a Rayleigh distribution if the components of the two-dimensional wind velocity vector are uncorrelated and normally distributed with equal variance. For details about this distribution, see Wikipedia - Rayleigh distribution. |
| Stable | A random variable is said to be stable (or to have a stable distribution) if it has the property that a linear combination of two independent copies of the variable has the same distribution, up to location and scale parameters. For details about this distribution, see Wikipedia - Stable distribution. |
| StudentT | |
| Weibull |