Timing in R: Best Practices for Accurate Measurements

Timing in R: Best Practices for Accurate Measurements

Key Points Benchmarking is measuring and comparing the performance of different code snippets or functions. You can use the rbenchmark package to benchmark your R code and compare their results in a table or a plot. You can use the benchmark function to run multiple expressions or functions multiple times and collect the results in a data frame. You can use the order function to sort the results by different criteria, such as elapsed time, user time, system time, or relative time. You can use user time, system time, elapsed time, and relative time to compare and improve your code performance. Do you want to learn how to make your R code faster and more efficient? Do you want to know how long it takes for your code to run and where the bottlenecks are? Do you want to impress your friends and teachers with data analysis skills? If you answered yes to these questions, this tutorial is for you! In this tutorial, you will learn how to measure the running time of your R code using different functio…