Dimitry Venger - Extreme Value Analysis | PyData Tel Aviv 2022

How do you use data from 15 years of observations to predict the magnitude of a “once in 50 years” storm? How can we build a network infrastructure that can handle the maximum traffic over a decade, using just one year of data?
Extreme value Analysis (EVA) provides a statistical and technical framework for the analysis of extreme deviation from the median of probability distributions. It is used in multiple fields to predict the probability of the recurrence of extreme outliers in data or even of the occurrence of heretofore unobserved phenomena.
This talk aims to provide the listener with a basic understanding of the analysis framework and the mathematical justification for its correctness. Numerous alternative routes, pitfalls and decision points encountered during analysis will be presented.
Currently, available libraries in Python allow only very rudimentary EVA, and many useful and sometimes necessary operations lack implementations. So while this talk is aimed at people hearing about EVA for the first time, it is also a call for contributors to implement those necessary features.
Slides: docs.google.com/presentation/...
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[@GeorgeZoto]

Interesting topic and well covered, thank you for sharing both the theoretical side of it as well as the code/implementation side. I appreciate the slides :)

[@diegoboyaca921]

What amazing explanation of the topic. Thanks for the presentation.

[@galenseilis5971]

The experimental module of PyMC supports the GEV distribution.

[@Oceansteve]

Thanks for the presentation.. I don’t think EVA gets enough discussion.

[@khalidmadrane]

The bridge collapse is in Europe, Genoa, not south America. Italy is a latin language speaking country but not a latino one 😉.