Probability theory and stochastic processes Definition
Coupling
Builds on Probability measureMarginal distributionRandom variableProbability space
Definition
Let be a probability measure on a measurable space and a probability measure on a measurable space . A coupling of and is a probability measure on the product space whose marginals are and : Equivalently, a coupling is a pair of random variables on one probability space with of law and of law . The joint law of such a pair is a coupling in the first sense.
Remarks
Example: the product measure is a coupling, the independent coupling. Indeed , and in the same way for the second marginal. Example: for , let be uniform on , and . Then and are Bernoulli with parameters and , and everywhere. Non-example: on , the point mass is not a coupling of two Bernoulli laws with parameter , because its first marginal is . If and the diagonal is measurable, every coupling satisfies the coupling inequality , where is the total variation distance.
Reading path
To understand this page from the ground up, read these 5 pages in order. The foundations come first.
Show the path as a graph
- no evidence level
- Marginal distribution concept
- Probability measure concept
- Probability space concept
- Random variable concept
- Coupling definition
Further reading
About this page
| Tag | TD7S2HF19H |
|---|---|
| URI | m2://TD7S2HF19H |
| Kind | definition |
| Writing | W0 stub |
| MSC | 60E05, 60E15 |
| Defines | Coupling |
| Uses | Probability measure, Marginal distribution, Random variable, Probability space |
| Changed | 2 November 2026 |
Markdown · JSON · Edit on GitHub
What this page needs for W1
- an inventory row: the row of the inventory that the node accounts for (0 of 1)
- a source with a locator (0 of 1)
The writing levels say how complete the text of a page is. They do not measure its truth.
What links here
No page links to this page yet.