-2
$\begingroup$

I'm trying to abstract the mathematical part of the problem as much as possible before the details follow, There's this dynamic data set that's $O(2^{32})$, a recent result described it as a power-law distribution, as average is approaching $1-2$ with a peak at $100$ as said. I was just motivated by the fact that there is a subset known to have sometimes values of $O(10^5)$ inside, and the 1st lesson on Statistics is that average is not enough to represent the data in such cases. Then I found previous results describing the same dataset as:

  • "is impossible to be modeled mathematically, since it is purely chaotic" (Stanford report Dec2015)

  • "Nevertheless, in the above graph there’s a distinct linear formation within the phenomenal chaos" (2017).

I came to this group to ask the Scientific opinion of the most specialized, all the complete files r downloadable & available online.

References

The Stanford Report poster

The median results 2017, although I think it has 2 groups/clusters one with a linearly increasing median & one adjacent to the X-axis (the majority by the newer results)

a fig From "Implementing A Church–Turing Deutsch Principle Machine on a Blockchain", Konstantinos Sgantzos,Department of Computer Science and Biomedical Informatics , University of Thessaly, Lamia, Greece,17-07-2017

The Utreexo graph 2019, with green text & colored lines added by me

. Ps. I added Laplace Transformation as a keyword because it is stated in the full copy of the Stanford report that it was used in processing the data set:

Two methods of doing this are either (1) entirely empirically or (2) based on a fitted distribution. The former case is simply a matter of sorting the lifespan dataset and splitting it into ten equally sized groups. The latter requires more processing. Understanding that the data should show signs of a Laplace or exponential distribution based the standard application of those distributions, the first step was to cluster the lifespan set using k-median (`1 penalty function) clustering. From there, we fitted either a Normal, Laplace, or Exponential (whichever was most likely) distribution to each cluster using maximum likelihood estimation and then formed a global distribution as a weighted sum.

$\endgroup$
3
  • $\begingroup$ I'm unsure what you mean by a "chaotic" data set? white noise? $\endgroup$ Jun 11, 2021 at 19:37
  • $\begingroup$ The term "Chaotic" came from the papers/reports not me, I understand it as "cannot be mathematically predicted or fitted in a known formula/distribution/curve/..."; usually refers to dynamic data $\endgroup$
    – ShAr
    Jun 11, 2021 at 20:52
  • $\begingroup$ Do u have an answer to the question? Howcome nobody in a math specialized group like this is willing to answer & clarify a scientific issue????Who just downgraded the Q without even answering it?!!!! $\endgroup$
    – ShAr
    Jun 15, 2021 at 1:02

1 Answer 1

1
$\begingroup$

I suggest exploring the alpha-stable models. Anytime, data are this skewed maybe that is the way to go. I would consult with John Nolan of American University, a real expert and a software writer in this area.

$\endgroup$
2
  • $\begingroup$ The curves here r quite different than both results I think?httpss://en.m.wikipedia.org/wiki/Stable_distribution $\endgroup$
    – ShAr
    Jun 17, 2021 at 18:12
  • $\begingroup$ Also, in general do u agree with me that it's kind of strange that the Utreexo team build their MIT licenced & widely funded project assuming most UTXOs will have lifespan 1-2 ( with a little peak at 100 as they say). When I pursued much on the discussion & found the Stanford report, they just stopped replying (in fact it seemed like everyone every where did so) $\endgroup$
    – ShAr
    Jun 17, 2021 at 19:24

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

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