BetaDistribution[\[Alpha], \[Beta]] represents a continuous beta distribution with shape parameters \[Alpha] and \[Beta].
Distributions defined in this package have been added to the built-in Mathematica kernel. The input syntax for UniformDistribution has changed. Random and RandomArray are ...
Bounded domain distributions naturally come up when random variables should only vary in a finite interval. Some distributions, like beta, occur in a variety of ways, ...
Mathematica's sophisticated algorithms for handling higher mathematical functions to arbitrary precision—and in symbolic form—immediately brings a new level of accuracy—and ...
KumaraswamyDistribution[\[Alpha], \[Beta]] represents a Kumaraswamy distribution with shape parameters \[Alpha] and \[Beta].
Likelihood[dist, {x_1, x_2, ...}] gives the likelihood function for observations x_1, x_2, ... from the distribution dist.
PERTDistribution[{min, max}, c] represents a PERT distribution with range min to max and maximum at c.PERTDistribution[{min, max}, c, \[Lambda]] represents a modified PERT ...
LogLikelihood[dist, {x_1, x_2, ...}] gives the log-likelihood function for observations x_1, x_2, ... from the distribution dist.
The functions described here are among the most commonly used discrete univariate statistical distributions. You can compute their densities, means, variances, and other ...
Version 6.0 introduced integrated highly efficient support for a wide range of statistical functions and operations, both on explicit data and on symbolic representations of ...