Probability theory and stochastic processes Stochastic processes: general theory Concept
Stopping time
Summary
A stopping time is a random time with the following property. At each time , one can decide whether has already happened using only the information available at time . First hitting times of sets by adapted processes are the main examples. Stopping times are central in martingale theory, through the optional stopping theorem, and in the strong Markov property and optimal stopping.
Where this leads
22 pages build on this one.
- Sequential analysis
- Wald–Wolfowitz optimality of the sequential probability ratio test
- Sequential probability ratio test
- Lévy's characterization of Brownian motion
- Kakutani's solution of the Dirichlet problem
- Wald's equation
- Optional stopping theorem
- Tanaka's formula
- Hunt process
- Reflection principle
- Semimartingale
- Stopped process
- Loop-erased random walk
- Burkholder–Davis–Gundy inequality
- Doob–Meyer decomposition theorem
- Secretary problem
- CUSUM
- Harmonic measure as exit distribution
- Skorokhod's embedding theorem
- Change detection
- Girsanov theorem
- Local martingale
Further reading
About this page
| Tag | WND87FBAKC |
|---|---|
| URI | m2://WND87FBAKC |
| Kind | concept |
| Writing | W0 stub |
| MSC | 60G40, 60G05 |
| Same as |
Markdown · JSON · Edit on GitHub
What this page needs for W1
- 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
Used by
- Sequential analysis
- Wald–Wolfowitz optimality of the sequential probability ratio test
- Sequential probability ratio test
- Kakutani's solution of the Dirichlet problem
- Wald's equation
- Optional stopping theorem
- Hunt process
- Reflection principle
- Stopped process
- Loop-erased random walk
- Burkholder–Davis–Gundy inequality
- Doob–Meyer decomposition theorem
- Secretary problem
- CUSUM
- Harmonic measure as exit distribution
- Skorokhod's embedding theorem
- Change detection
- Local martingale