#164
in
Python
"Calculating Pi with Darts by Physics Girl [and Veritasium Derek] (PBS LearningMedia)"
https://youtube.com/watch?v=M34TO71SKGk
Monte Carlo method: https://en.wikipedia.org/wiki/Monte_Carlo_method
"Inferred value of Pi is never 3.1415" (with pymc) https://discourse.pymc.io/t/inferred-value-of-pi-is-never-3-... https://github.com/pymc-devs/pymc
I believe the pymc versions were resolved into developing version 4 of pymc. Development at https://github.com/pymc-devs/pymc
It still depends on theano now evolved and renamed https://aesara.readthedocs.io/en/latest/
Current pyro has a Monte Carlo sampler
https://docs.pyro.ai/en/stable/_modules/pyro/infer/mcmc/nuts...
I'm surprised the article suggested BUGS instead of JAGS. JAGS has pretty much all of the features of BUGS (except a GUI) and is open source, cross platform, faster, and easy to run batch jobs from the command line. I've been using JAGS pretty much everyday for the past 1.5 years for a research project I'm working on and have grown quite fond of it. Before that, I was using BUGS for 6 months and was in a living hell with how slow fitting models with it was. Since switching to JAGS, my productivity has increased by several orders of magnitude. I'm primarily using it for analyzing Markov Chain Monte Carlo models of behavioral data where standard nonlinear optimization techniques (such as MLE and MAP) are impossible to use.
Here's a link to JAGS's homepage: http://mcmc-jags.sourceforge.net/
There's also PyMC (which can do similar types of analysis). https://github.com/pymc-devs/pymc