Krylov–Bogolyubov theorem: Difference between revisions

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In [[mathematics]], a '''Bessel process''', named after [[Friedrich Bessel]],<!-- Why is it named after him? --> is a type of [[stochastic process]]. The Bessel process of order ''n'' is the [[real number|real-valued]] process ''X'' given by
 
:<math>X_t = \| W_t \|,</math>
 
where ||·|| denotes the [[Norm (mathematics)#Euclidean norm|Euclidean norm]] in '''R'''<sup>''n''</sup> and ''W'' is an ''n''-dimensional [[Wiener process]] ([[Brownian motion]]) started from the origin.
The n-dimensional Bessel process is the solution to the  [[stochastic differential equation]]
 
:<math>dX_t = dZ_t + \frac{n-1}{2}\frac{dt}{X_t}</math>
where ''Z'' is a ''1''-dimensional [[Wiener process]] ([[Brownian motion]]). Note that this SDE makes sense for any real parameter <math>n</math> (although the drift term is singular at zero). Since ''W'' was assumed to have started from the origin the initial condition is ''X''<sub>0</sub>&nbsp;=&nbsp;0.
 
For ''n''&nbsp;≥&nbsp;2, the ''n''-dimensional Wiener process is [[Markov chain#Recurrence|transient]] from its starting point: [[almost surely|with probability one]], ''X''<sub>''t''</sub>&nbsp;&gt;&nbsp;0 for all ''t''&nbsp;&gt;&nbsp;0.  It is, however, neighbourhood-recurrent for ''n''&nbsp;=&nbsp;2, meaning that with probability&nbsp;1, for any ''r''&nbsp;>&nbsp;0, there are arbitrarily large ''t'' with ''X''<sub>''t''</sub>&nbsp;<&nbsp;''r''; on the other hand, it is truly transient for ''n''&nbsp;>&nbsp;2, meaning that ''X''<sub>''t''</sub>&nbsp;≥&nbsp;''r'' for all ''t'' sufficiently large.
 
A notation for the Bessel process of dimension ''n' started at zero is BES<sub>0</sub>(n).
 
0 and 2 dimensional Bessel processes are related to local times of Brownian motion via the Ray-Knight theorems.<ref>{{cite book |first=D. |last=Revuz |first2=M. |last2=Yor |title=Continuous Martingales and Brownian Motion |publisher=Springer |location=Berlin |year=1999 |isbn=3-540-52167-4 }}</ref>
 
The law of a Brownian motion near x-extrema is the law of a 3 dimensional Bessel process (theorem of Tanaka).
 
==References==
{{Reflist}}
 
*{{cite book | author=Øksendal, Bernt | title=Stochastic Differential Equations: An Introduction with Applications | publisher=Springer |location=Berlin | year=2003 | isbn=3-540-04758-1}}
*Williams D. (1979) ''Diffusions, Markov Processes and Martingales, Volume 1 : Foundations.'' Wiley. ISBN 0-471-99705-6.
 
{{Stochastic processes}}
 
[[Category:Stochastic processes]]
 
 
{{probability-stub}}

Revision as of 16:46, 20 April 2013

In mathematics, a Bessel process, named after Friedrich Bessel, is a type of stochastic process. The Bessel process of order n is the real-valued process X given by

Xt=Wt,

where ||·|| denotes the Euclidean norm in Rn and W is an n-dimensional Wiener process (Brownian motion) started from the origin. The n-dimensional Bessel process is the solution to the stochastic differential equation

dXt=dZt+n12dtXt

where Z is a 1-dimensional Wiener process (Brownian motion). Note that this SDE makes sense for any real parameter n (although the drift term is singular at zero). Since W was assumed to have started from the origin the initial condition is X0 = 0.

For n ≥ 2, the n-dimensional Wiener process is transient from its starting point: with probability one, Xt > 0 for all t > 0. It is, however, neighbourhood-recurrent for n = 2, meaning that with probability 1, for any r > 0, there are arbitrarily large t with Xt < r; on the other hand, it is truly transient for n > 2, meaning that Xt ≥ r for all t sufficiently large.

A notation for the Bessel process of dimension n' started at zero is BES0(n).

0 and 2 dimensional Bessel processes are related to local times of Brownian motion via the Ray-Knight theorems.[1]

The law of a Brownian motion near x-extrema is the law of a 3 dimensional Bessel process (theorem of Tanaka).

References

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  • Williams D. (1979) Diffusions, Markov Processes and Martingales, Volume 1 : Foundations. Wiley. ISBN 0-471-99705-6.

Template:Stochastic processes


Template:Probability-stub

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