4
$\begingroup$

I think that the definition of fractional Brownian Motion is widely known (for example as a Gaussian Process with particular variance covariance stucture parametrized by the so-called Hurst index).

Heuristically, you can think of those processes as Gaussian processes with long (or short) memory depending on the value of their Hurst Index, and for Hurst index equal to 1/2 you get classical Brownian Motion (which has no memory).

I was wondering what would be the definition for "fractional Poisson Processes" and what stylised facts about fractional Brownian Motion one should consider in extending the definition to Poisson process.

If any reference exists about this, this is just fine for me.

I have no other motivation than curiosity on this topic.

$\endgroup$
2
  • 3
    $\begingroup$ A google search for fractional Poisson process gives a lot of results. Fractional Brownian motion is weird enough, with stochastic integrals no longer being martingales; yuck. $\endgroup$
    – Alex R.
    Jan 25 '11 at 18:49
  • $\begingroup$ True but google doesn't tell us what are the best papers or the "level" associated with them ... Moreover an answer which indicates the canonical properties of the fBM that should be extended in order to get a fractional Poisson process would give a great insight before reading google's results on fPP Best Regards $\endgroup$
    – The Bridge
    Jan 26 '11 at 7:25
4
$\begingroup$

A standard Poisson process is a renewal process with exponential distributed waiting times. Fractional Poisson process (FPP) is also a renewal process with Mittag-Leffler waiting times. Note that Mittag-Leffler distribution is a heavy tailed generalization of exponential distribution. Further, let N(t) be a standard Poisson process and $E_{\alpha}(t) = \inf\{s \geq 0: S_{\alpha}(s)>t\}$ be the first-exit time of a stable subordinator $S_{\alpha}(t)$ then the time-changed process $N^*(t) = N(E_{\alpha}(t))$ is also a characterization of FPP.

$\endgroup$
4
$\begingroup$

Here is a thesis containing (in Section 2) an overview of different definitions of fPP.

My personal favorite is the "Standard Fractional generalization I" defined in 2.2. The reason is that there seems to be (I failed to find any relevant results) an isomorphism between this version and fBm similar to the (usual) Wiener-Poisson isomorphism.

$\endgroup$
2
  • $\begingroup$ The link doesn't work. Could you please tell me author and title of the thesis? $\endgroup$
    – user74045
    Mar 24 '16 at 22:48
  • $\begingroup$ @user74045, the name is Dexter Cahoy. I've updated the link. $\endgroup$
    – zhoraster
    Mar 25 '16 at 4:35
2
$\begingroup$

Hello Everyone,

To find the definition of Fractional Poisson Process and its first two moments as well as the Compound Fractional Poisson Process go to http://pi.314159.ru/laskin3.pdf To find more on the topic you may Google with key words: fractional Poisson distribution. I hope it helps.

$\endgroup$
0
$\begingroup$

I came across two possibilities when it comes to introducing fractionality:

1) Subordination by inverse $\alpha$-stable subordinator $(E_\alpha(t))$ (see for example [1]): $N(E_\alpha(t))$ is equivalently derived from the renewal representation of the Poisson process and replaces the exponential distribution of the waiting times by the Mittag-Leffler distribution.
Moreover, the inverse subordinator method can also be applied to Brownian motion, which gives $B(E_\alpha(t))$. This stochastic process is self-similar, but does no longer have stationary increments as $(E_\alpha(t))$ has not.

2) Let's assume we have the fBM as defined in on Wiki. The suggested fPP in [2] starts with the Weyl integral representation of fBM and replaces the integration w.r.t. Brownian motion by integration w.r.t. a Poisson process. In this case both fBM and fPP are self-similar and have stationary increments.

References:

[1] Meerschaert, M. M. and P. Straka (2013). Inverse stable subordinators. Math. Model. Nat. Phenom. 8 (2), 1–16.

[2] Wang, X.-T., Z.-X. Wen, and S.-Y. Zhang (2006). Fractional Poisson process. II. Chaos Solitons Fractals 28 (1), 143–147.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.