In almost every area where probability and statistics are used there have been found a few parametric distribution families that are known to be good models. The origins vary ...
Discrete distributions come from a variety of backgrounds, but perhaps the most common relate back to the simple Bernoulli trial, which chooses between two outcomes, called ...
The fundamental type of distribution in reliability analysis is a lifetime distribution. This models the lifetime of a component or a system. Many lifetime distributions are ...
BernoulliDistribution[p] represents a Bernoulli distribution with probability parameter p.
MultinomialDistribution[n, {p_1, p_2, ..., p_m}] represents a multinomial distribution with n trials and probabilities p_i.
MomentGeneratingFunction[dist, t] gives the moment generating function for the symbolic distribution dist as a function of the variable t. MomentGeneratingFunction[dist, ...
DistributionParameterAssumptions[dist] gives a logical expression for assumptions on parameters in the symbolic distribution dist.
DistributionParameterQ[dist] yields True if dist is a valid distribution, and yields False otherwise.
InverseCDF[dist, q] gives the inverse of the cumulative distribution function for the symbolic distribution dist as a function of the variable q.
Likelihood[dist, {x_1, x_2, ...}] gives the likelihood function for observations x_1, x_2, ... from the distribution dist.