Sjors Provoost @sjors@m.sprovoost.nl
Allow me to plug https://pletdecurve.nl here as well. It displays a "fire chart", as Yaneer Bar-Yam from endcoronavirus.org calls them, for all Dutch provinces. You can drill down on a province to see how its municipalities are doing.
Built with Ruby on Rails, initially hosted on Heroku, but I moved it to my own Ubuntu server, which was easier than I expected.
It's open source, and should be easy to adapt to other countries; happy to accept PR's to make maintaining a fork easier.
Meanwhile Draper is still actively putting lives at risk, both through his direct actions and insane policy recommendations. But clearly getting people killed is fine by Twitter policy. As long as there are no guns involved.
Which brings us to the S&P chart. If it was Gaussian, it should stay under the blue line. It's not even close, so it must a scarier distribution. But what's in the chart?
Well we can plough through 3 pages of Taleb's math, or check Wikipedia for (non nuclear war) MAD: "In other words, for a normal distribution, mean absolute deviation is about 0.8 times the standard deviation"
That's where the sqrt(π/2) blue line comes from. QED-ish; not a normal distribution.
First thing to understand is that there's hierarchy of statistical distributions, our high school friend Gaussian being near the friendly bottom.
Unless you understand the underlying process, like in some areas of physics, you can measure all you like, but you can't prove something is in the lower left. You can however *disprove* it, often with a single observation (after you check your instruments). Falsification at work.
As you disprove friendly distributions like Gaussian, you move up.
Why the S&P 500 is not Gaussian
I'm trying to keep up with Taleb's new technical book, but I have neither his background in trading nor mathematical rigor. In a previous life I was a physicist; they are notorious for skipping math steps based on intuition, expecting mathematicians will prove their intuition correct.
I may do some out loud thinking here, starting with a TL&DR of this chart.
The book Statistical Consequences of Fat Tails is here: https://www.academia.edu/37221402/STATISTICAL_CONSEQUENCES_OF_FAT_TAILS_TECHNICAL_INCERTO_COLLECTION_
"Naive Probabilism" - Harry Cane
For the less mathematically inclined I recommend this essay. It may save your life, as it tells you which pundits and policy makers you should assume are dangerously incompetent.
https://www.researchers.one/article/2020-03-9
The bird site just locked my account and censored my tweet. In case anyone wants a statement (you never know):
"If Twitter apparatchiks are OK with a call to global genocide by negligence, in order to boost the stock market, but is not OK with asking someone to try their own advice first, then go fuck yourself."
Also note how I didn't say "I hope you and your family get infected", so it's not even actually a violation of their policy. But whatever, now I have time to read Talebs new book.
I wanted something bigger to run my node on. Is it overkill? Yes! Do you really need that much CPU cooling for a server? Maybe.
Before: Khadas VIM2 Max with 256 GB SD card for blockdir, which ran out of space a week ago. It was also just unstable: randomly declaring blocks invalid and crashing, especially when connected to network cable. https://www.khadas.com/vim
After: Intel i5, 32 GB RAM, 512 GB SSD (using PCIe connector at the bottom of the motherboard). Case: Thermaltake Core V1
