A stopping time with respect to a sequence of random variables X1, X2, ... is a random variable with the property that for each t, the occurrence or non-occurrence of the event = t depends only on the values of X1, X2, ..., Xt. In some cases, the definition specifies that Pr( < ∞) = 1, or that be almost surely finite, although in other cases this requirement is omitted.
Another, more general definition may be given in terms of a filtration: Let be an ordered index set (often or a compact subset thereof), and let be a filtered probability space, i.e. a probability space equipped with a filtration. Then a random variable is called a stopping time if for all in . Often, to avoid confusion, we call it a -stopping time and explicitly specify the filtration. Speaking concretely, for to be a stopping time, it should be possible to decide whether or not has occurred on the basis of the knowledge of, i.e., event is -measurable.
Stopping times occur in decision theory, in which a stopping rule is characterized as a mechanism for deciding whether to continue or stop a process on the basis of the present position and past events, and which will almost always lead to a decision to stop at some time.
Read more about Stopping Time: Examples, Localization, Types of Stopping Times
Famous quotes containing the words stopping and/or time:
“Research is usually a policeman stopping a novel from progressing.”
—Brian Moore (b. 1921)
“The conqueror at least; who, ere Time renders
His last award, will have the long grass grow
Above his burnt-out brain and sapless cinders.
If I might augur, I should rate but low
Their chances: they are too numerous, like the thirty
Mock tyrants, when Rome’s annals wax’d but dirty.”
—George Gordon Noel Byron (1788–1824)