Feynman vs. Computer; renewing GPG subkeys; Mallows is stuck in his chamber!
Quick look at renewing GPG subkeys, before we dive into the basics of Monte Carlo integration which is oh-so-useful – and simple.
You have arrived at the mid-week hump. Have a $container of $beverage and enjoy some reading before you speed along with the rest of your life.
New articles
Renewing GPG Subkeys in 2025
I renewed my GPG subkeys recently, and this was the process.
Full article (1–4 minute read): Renewing GPG Subkeys in 2025
Feynman vs. Computer
A controversially-titled quick look at the basics of Monte Carlo methods for integration.
Full article (7–22 minute read): Feynman vs. Computer
Flashcard of the week
On the topic of Monte Carlo methods! One of the tricks to making them more efficient is drawing numbers from specific distributions rather than uniformly. (This ensures samples are taken where they matter more.) Some distributions are easy to draw from (exponential, logistic) others are more difficult (beta, normal).
Name an algorithm to draw from stable distributions.
Stable distributions are a generalisation of the normal distribution. They are the distributions one gets when making the tails of the normal distribution fatter. A special case is at alpha=2 which is the normal distribution, and then alpha=1 is the Cauchy distribution. The alpha refers to the tail index of the corresponding power law. Typical Pareto-style laws have a tail index around 1.5.
Anyway, one of the algorithms to efficiently draw from stable distributions is called
Chambers–Mallows–Stuck
And although I've never needed to implement this, I'm somehow able to remember the name because it paints a picture in my head of a scholar named Mallows up in their chamber, stuck working on difficult problems.
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