Comparing Performance in R Using Microbenchmark
This post is a very simple display of how to use microbenchmark in R . Other sites might have longer and more detailed posts , but this post is primarily to 'spread the word' about this useful function, and show how to plot it. An alternative version of this post exists in Microsoft's Azure Notebooks, as Performance Testing Results with Microbenchmark Load Libraries Memoise as part of the code to test, microbenchmark to show usage, and ggplot2 to plot the result. library(memoise) library(microbenchmark) library(ggplot2) Create Functions Generate several functions with varied performance times, a base function plus functions that leverage vectorization and memoisation. # base function monte_carlo = function(N) { hits = 0 for (i in seq_len(N)) { u1 = runif(1) u2 = runif(1) if (u1 ^ 2 > u2) hits = hits + 1 } return(hits / N) } # memoise test function monte_carlo_memo <- memoise(mon...