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Compound, infinitely divisible, and convolved distributions

9 articles

Beta negative binomial distribution

The beta negative binomial distribution (BNB) is a three-parameter count distribution formed when a negative binomial success probability follows a beta distribution, giving heavier tails than the negative binomial.

Beta-binomial distribution

The beta-binomial distribution is a discrete distribution for binomial counts whose success probability is drawn from a beta distribution, used to model overdispersion in count data.

Compound probability distribution

A compound probability distribution, also called a compound distribution, is the distribution of a sum of a random number of random variables, used to model insurance claims.

Convolution of probability distributions

The convolution of probability distributions is the operation that gives the distribution of the sum of independent random variables, central to probability theory and first applied by Laplace in 1781.

Dirichlet-multinomial distribution

The Dirichlet-multinomial distribution, also known as the multivariate Pólya distribution, is a probability distribution for count vectors whose category probabilities are drawn from a Dirichlet distribution.

Indecomposable distribution

An indecomposable distribution, also called an indecomposable probability distribution, is one that cannot be written as a convolution of two non-degenerate distributions, like prime numbers.

Infinite divisibility (probability)

Infinite divisibility, also called an infinitely divisible distribution, is a probability distribution representable as a sum of n independent, identically distributed variables for every n.

Mixture distribution

A mixture distribution is a probability distribution formed as a weighted combination of component distributions, equivalent to choosing a component at random and then sampling from it.

Stable distribution

The stable distribution, or Lévy alpha-stable distribution, is a probability distribution whose shape is preserved under addition; it includes the normal, Cauchy, and Lévy distributions as closed-form cases.