Sample continuous process

Sample continuous process

In mathematics, a sample continuous process is a stochastic process whose sample paths are almost surely continuous functions.

Definition

Let (Ω, Σ, P) be a probability space. Let "X" : "I" × Ω → "S" be a stochastic process, where the index set "I" and state space "S" are both topological spaces. Then the process "X" is called sample continuous (or almost surely continuous, or simply continuous) if the map "X"("ω") : "I" → "S" is continuous as a function of topological spaces for P-almost all "ω" in "Ω".

In many examples, the index set "I" is an interval of time, [0, "T"] or [0, +∞), and the state space "S" is the real line or "n"-dimensional Euclidean space R"n".

Examples

* Brownian motion (the Wiener process) on Euclidean space is sample continuous.
* For "nice" parameters of the equations, solutions to stochastic differential equations are sample continuous. See the existence and uniqueness theorem in the stochastic differential equations article for some sufficient conditions to ensure sample continuity.
* The process "X" : [0, +∞) × Ω → R that makes equiprobable jumps up or down every unit time according to

::egin{cases} X_{t} sim mathrm{Unif} ({X_{t-1} - 1, X_{t-1} + 1}), & t mbox{ an integer;} \ X_{t} = X_{lfloor t floor}, & t mbox{ not an integer;} end{cases}

: is "not" sample continuous. In fact, it is surely discontinuous.

Properties

* For sample-continuous processes, the finite-dimensional distributions determine the law, and vice versa.

ee also

* Continuous stochastic process

References

* cite book
author = Kloeden, Peter E.
coauthors = Platen, Eckhard
title = Numerical solution of stochastic differential equations
series = Applications of Mathematics (New York) 23
publisher = Springer-Verlag
location = Berlin
year = 1992
pages = pp. 38–39;
isbn = 3-540-54062-8


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