Numerics.
            
            The Numerics.NET.Statistics.Distributions namespace contains classes that represent statistical probability distributions.
Classes
| Arcsine | Represents the arcsine distribution. | 
| Bernoulli | Represents the Bernoulli distribution. | 
| Beta | Represents the Beta distribution. | 
| Binomial | Represents the binomial distribution. | 
| Burr | Represents the type XII Burr distribution. | 
| Cauchy | Represents the Cauchy distribution. | 
| Chi | Represents a chi distribution. | 
| Chi | Represents a chi-squared distribution. | 
| Continuous | Represents a continuous probability distribution. | 
| Continuous | Represents a continuous uniform distribution over an interval. | 
| Dirichlet | Represents a Dirichlet distribution. | 
| Discrete | Represents a discrete probability distribution. | 
| Discrete | Represents a probability distribution over a countable set of objects. | 
| Discrete | Represents a discrete uniform distribution over an interval. | 
| Distribution | Represents a statistical distribution. | 
| Erlang | Represents an Erlang distribution. | 
| Exponential | Represents an exponential distribution. | 
| FDistribution | Represents the F distribution. | 
| Folded | Represents a folded normal distribution. | 
| Gamma | Represents the Gamma distribution. | 
| Gaussian | Represents a multivariate distribution that is a mixture of multivariate normal distributions. | 
| Generalized | Represents the Generalized Pareto distribution. | 
| Generic | Represents a discrete probability distribution with arbitrary probabilities. | 
| Geometric | Represents the geometric distribution. | 
| Gumbel | Represents the Gumbel distribution. | 
| Hyperbolic | Represents the hyperbolic distribution. | 
| Hyperbolic | Represents a hyperbolic secant distribution. | 
| Hypergeometric | Represents a hypergeometric distribution. | 
| Inverse | Represents an inverse chi-squared distribution. | 
| Inverse | Represents the inverse Gamma distribution. | 
| Inverse | Represents the inverse Gaussian distribution. | 
| Inverse | Represents the inverse inverse Weibull distribution or Fréchet distribution. | 
| Johnson | Represents the Johnson distribution. | 
| Laplace | Represents a Laplace distribution. | 
| Logarithmic | Represents the logarithmic series distribution. | 
| Logistic | Represents the logistic distribution.. | 
| Log | Represents the log-logistic distribution. | 
| Lognormal | Represents the Log Normal distribution. | 
| Maxwell | Represents the Maxwell distribution. | 
| Multivariate | Represents a multivariate continuous probability distribution. | 
| Multivariate | Represents a multivariate normal distribution. | 
| Negative | Represents the negative binomial distribution. | 
| Non | Represents the non-central Beta distribution. | 
| Non | Represents a non-central chi-squared distribution. | 
| Non | Represents the non-central F distribution. | 
| Non | Represents the non-central Student t distribution. | 
| Normal | Represents a normal distribution. | 
| Normal | Represents the normal-inverse Gaussian distribution. | 
| Pareto | Represents the Pareto distribution. | 
| Pert | Represents a PERT distribution. | 
| Piecewise | Represents a continuous distribution with a piecewise linear distribution function. | 
| Poisson | Represents a Poisson distribution. | 
| Random | Contains extensions to random number functions that use statistical distributions. | 
| Rayleigh | Represents the Rayleigh distribution. | 
| Student | Represents the Student t distribution. | 
| Transformed | Represents the transformed Beta distribution. | 
| Transformed | Represents the transformed Gamma distribution. | 
| Triangular | Represents the triangular distribution. | 
| Truncated | Represents a continuous probability distribution restricted to a portion of its domain. | 
| Weibull | Represents the Weibull distribution. | 
| Wishart | Represents a multivariate Wishart distribution. | 
| Zipf | Represents a Zipf distribution. | 
| Zipfian | Represents a Zipfian distribution. | 
Enumerations
| Distribution | Enumerates the capabilities of a probability distribution. | 
| Estimation | Represents the possible methods for estimating the parameters of a distribution. | 
| Gumbel | Specifies whether the Gumbel distribution models the smallest or largest extreme values. | 
| Johnson | Enumerates the types of the Johnson system of probability distributions. | 
| Pareto | Enumerates the variants of the Pareto distribution. |