Probability theory and stochastic processes Markov processes Concept
Diffusion process
Summary
A diffusion process is a Markov process with continuous paths, such as Brownian motion with a drift and a variable volatility. Its local behaviour is described by a drift vector and a diffusion matrix. Its generator is a second-order differential operator, so diffusions connect probability with parabolic and elliptic partial differential equations. Most diffusions are built as solutions of stochastic differential equations.
Where this leads
1 page builds on this one.
Further reading
About this page
| Tag | 9HDQ094ADQ |
|---|---|
| URI | m2://9HDQ094ADQ |
| Kind | concept |
| Writing | W0 stub |
| MSC | 60J60, 60H10 |
| Specializes | Stochastic process |
| Same as | |
| 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.