Mira Celine Klein continues a series on code performance in R:
This is the second part of our series about code performance in R. It contains a lot of approaches to reduce the time your code needs to run. It’s useful to know those ideas before starting to write new code, but it also helps to optimize existing code.
If you have already written some code you want to speed up, but don’t know which part of it is actually slow, I recommend you to read the first part of this series on profiling. That article also introduces the microbenchmark package which we are going to use to measure code performance in this article.
Let’s start with a seemingly obvious rule, which is however not always easy to follow.
Read on for some tips. H/T R-bloggers.