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In [[probability]] theory, a '''stable process''' is a type of [[stochastic process]]. It includes stochastic processes whose associated [[probability distribution]]s are stable distributions.<ref name=essentials/>

Examples of stable processes include the [[Wiener process]], or [[Brownian motion]], whose associated probability distribution is the [[normal distribution]]. They also include the [[Cauchy process]]. For the symmetric Cauchy process, the associated probability distribution is the [[Cauchy distribution]].<ref name=essentials/>

The degenerate case, where there is no random element, i.e., <math>X(t) = mt</math>, where <math>m</math> is a constant, is also a stable process.<ref name=essentials>{{cite book|title=Essentials of Stochastic Processes|author=Ito, K.|pages=50–55|publisher=American Mathematical Society|year=2006|isbn=9780821838983}}</ref>

==References==
{{reflist}}

{{Stochastic processes}}



[[Category:Probability theory]]