- Mathematical modeling
- >
- Statistical models
- >
- Probability distributions
- >
- Systems of probability distributions

- Measure theory
- >
- Measures (measure theory)
- >
- Probability distributions
- >
- Systems of probability distributions

- Measure theory
- >
- Probability theory
- >
- Probability distributions
- >
- Systems of probability distributions

- Probability
- >
- Probability theory
- >
- Probability distributions
- >
- Systems of probability distributions

- Statistical theory
- >
- Statistical models
- >
- Probability distributions
- >
- Systems of probability distributions

- Statistics
- >
- Statistical theory
- >
- Probability distributions
- >
- Systems of probability distributions

Copula (probability theory)

In probability theory and statistics, a copula is a multivariate cumulative distribution function for which the marginal probability distribution of each variable is uniform on the interval [0, 1]. Co

(a,b,0) class of distributions

In probability theory, a member of the (a, b, 0) class of distributions is any distribution of a discrete random variable N whose values are nonnegative integers whose probability mass function satisf

Vine copula

A vine is a graphical tool for labeling constraints in high-dimensional probability distributions. A regular vine is a special case for which all constraints are two-dimensional or conditional two-dim

Mixture distribution

In probability and statistics, a mixture distribution is the probability distribution of a random variable that is derived from a collection of other random variables as follows: first, a random varia

Quantile-parameterized distribution

Quantile-parameterized distributions (QPDs) are probability distributions that are directly parameterized by data. They were motivated by the need for easy-to-use continuous probability distributions

Metalog distribution

The metalog distribution is a flexible continuous probability distribution designed for ease of use in practice. Together with its transforms, the metalog family of continuous distributions is unique

Pearson distribution

The Pearson distribution is a family of continuous probability distributions. It was first published by Karl Pearson in 1895 and subsequently extended by him in 1901 and 1916 in a series of articles o

Tweedie distribution

In probability and statistics, the Tweedie distributions are a family of probability distributions which include the purely continuous normal, gamma and inverse Gaussian distributions, the purely disc

© 2023 Useful Links.