Even faster matrix math in R on macOS with M1

Instructions for switching R to use Apple’s math library optimized for Apple Silicon and some benchmarks comparing the performance.

Approximating probabilities

A tutorial on using R and Monte Carlo simulation as a substitute for analytical solutions to “what is the probability of?” problems.

Faster matrix math in R on macOS

Update (October 2021): macOS 10.14 “Big Sur” and later do not ship with Accelerate BLAS dynamic libraries in the filesystem, so this trick only works up to macOS 10.13 “High Sierra”

If you want faster matrix operations in R on your Mac, you can use Apple’s BLAS (Basic Linear Algebra Subprograms) library from their Accelerate framework instead of the library which comes with the R binary that you get from CRAN. (Unless you built R from source yourself.) CRAN recommends against this, saying:

Modeling a logic puzzle as a constraint satisfaction problem with OMPR

A tutorial on treating a logic puzzle as constraint satisfaction problem and coding it as an integer program to solve using the R package {ompr}.

Bayesian Optimization in R

A tutorial on using Bayesian optimization to find the minimum of a function with only a few evaluations of the functions, using different approaches to identify the best next value to evaluate the function at.