Open JulienSiems opened 2 years ago
Hi Julien!
You can cite this zenodo link, which has a doi, or the paper associated with it (there is a link on the zenodo page)
https://zenodo.org/record/53787#.Yb8KzEYo-Nx
I realize that it has an old version, I.e. not synced with github. When I come back from vacations in a week I will update it, if you want to wait.
Best, and thanks, José
On Thu, 16 Dec 2021, 17:57 Julien, @.***> wrote:
I am using your code and it would be good to able to cite your repo! Could you post how you'd like it to be cited?
Thanks for your great work!
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Hi José,
Great, no rush! Let me know once you have updated it. I am pretty surprised how well fitting a stable distribution via your tabulated values works. I compared against a more classical estimator for the tail index for samples of a stable distribution with different tail indices and skewness and your estimator was an order of magnitude more accurate in terms of mean absolute error.
I did notice some outliers in the estimation, though. It may help to implement retries for the optimization in scipy or use evolutionary algorithm, like differential evolution, rather than gradient-based optimization?
Best, Julien
Hi,
It is surprising indeed haha. I don't know what estimators you are using but the classic problem there is to choose a boundary for the tail.
Can I ask you for what are you using it?
Best, José
On Sun, 19 Dec 2021, 12:09 Julien, @.***> wrote:
Hi José,
Great, no rush! Let me know once you have updated it. I am pretty surprised how well fitting a stable distribution via your tabulated values works. I compared against a more classical estimator for the tail index for samples of a stable distribution with different tail indices and skewness and your estimator was an order of magnitude more accurate in terms of mean absolute error.
Best, Julien
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Hi José,
but the classic problem there is to choose a boundary for the tail.
Do you mean to find the tail index by fitting an exponential decay to the tails?
I am using this one: https://link.springer.com/article/10.1007/s00184-014-0515-7 (Corollary 2.4) It's for example used quite extensively in: https://arxiv.org/abs/1901.06053 Below, is the plot I meant for the absolute alpha estimation error for different stable samples.
Best,
Julien
I am using your code and it would be good to able to cite your repo! Could you post how you'd like it to be cited?
Thanks for your great work!