AlexTCH
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Что-то про программирование, что-то про Computer Science и Data Science, и немного кофе. Ну и всякая чушь вместо Твиттера. :)
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https://statmodeling.stat.columbia.edu/2020/07/02/no-i-dont-believe-that-claim-based-on-regression-discontinuity-analysis-that/

A great post with thorough replication/reanalysis/discussion and we might say debunking. Also an example of pretty decent scientific discussion. Plus deep technical dives in the comments.

#statistics #rdd
На днях летел в Airbus A319 — приятно сознавать, что софт, им управляющий, был верифицирован (в разных отношениях) и собран CompCert. 😏
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Нашёл в темнушке старый обоссаный котами бокен.
Атака +20
Привлекательность -50
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Когда в 2005 читал "Метро 2033" казалось, что автор установил дату ядерного апокалипсиса слишком близко... 😏
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А вообще, про "Метро" вспомнил в связи с "локативным искусством" (привязанным к местности) — пока не покатался на московском метро, роман как-то не резонировал примерно никак.
https://www.youtube.com/watch?v=CuxfRdjfZG0
Oldie but goodie. Curious highlights.

Climate models have surprisingly low error rates in terms of software bugs. It's nice that people really can and do produce high-quality software without Sales and Marketing pressure. 😏

The models systematically overestimate some parameters but underestimate others. Thus when you see graphs projecting climate into the far future, actual air temperatures are likely to be a bit lower (while deep ocean temperatures will be higher). And the see levels are likely to be higher than predicted which is not very nice.
Make sense not war
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https://github.com/stan-dev/stanc3

The new(ish, compared to the previous one) (source-to-source) compiler for the Stan language is implemented in OCaml and became the default one quite some time ago. The Readme also has a reference to a discussion "OCaml vs. Rust". Mind that the discussion take place back in 2018 (4 years ago! 😱) and you can appreciate how much Rust has matured during the time.

And Stan is a huge (by impact) project in the area of Bayesian modeling, statistical analysis and inference.
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And speaking about statistics...

https://statmodeling.stat.columbia.edu/2022/11/08/dying-children-and-post-publication-review-rectal-suppositories-edition/

Sloppy statistical analysis indeed jeopardizes lives of actual children in Africa. 😞
Attempting to prove any nontrivial theorem about your program will expose lots of bugs: The particular choice of theorem makes little difference!

LOL, so true! 😂
From https://statmodeling.stat.columbia.edu/2022/11/09/simulation-based-calibration-checking-sbc-is-stronger-than-you-thought-and-the-sbc-package-in-r/#comment-2122385
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Кот — не карась, не харрась кота!
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Настолько старый и нишевый, что успел подержать первый печатный сборник пирожков. : 🏆
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https://lawrencecpaulson.github.io/2022/10/12/verifying-distributed-systems-isabelle.html

A guest post by Martin Kleppmann on Lawrence Paulson's blog. Martin explains the basics of distributed algorithms verification in Isabelle/HOL. As the main tools he employs (heavily parametrized) functions, maps (which are secretly functions too), inductive predicates and inductive proofs with a slightly custom induction principle (and variable generalization).
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If for some weird reason you decided to write something a layperson can understand there's a tool to help you: https://splasho.com/upgoer6/

On the other hand you can reverse it and try to come up with the most obscure words no one knew were out there! 😂
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Software Requirements Specification to specification is what meta-irony to irony.
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Чтобы научиться ездить на велосипеде нужны дополнительные колёсики. Такие, которые внутрь принимают.
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— Утром — кофе, вечером — код!
— А можно наоборот?
— Можно. Но кофе вперёд.
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— А вот тут вы можете видеть глистограмму.
— Может, гистограмму?
— Нет.
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A Christmas tree with really big balls!
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Uncute anxiety
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