Gaussian processes like you never saw them
This post was written in a Jupyter notebook, which can be found here The Python code below is heavily inspired by the Javascript implementation here
A big uniform
This post was inspired by something Brendon Brewer said on the ESAC Data Analysis & Statistics Workshop, last week.
Bricks
Chaos in the Brickyard, by Bernard K. Forscher, Mayo Clinic, Rochester, Minnesota • link
Time derivative of the Keplerian function
I started experimenting with the automatic differentiation package autograd and, wow this thing is pretty amazing!
Truncated Distributions
In a Bayesian model, each parameter needs a prior distribution. To set these priors, we sometimes want to use standard probability distributions but constrained to some interval \([a,b]\) inside their support. How to do this?