microbenchmark is provided as part of an R library. Once included in your script you then surround the code in question with a microbenchmark tag and once executed the tool will output profiling information for the script in question.

For example, we could have this use:

library(microbenchmark)
x <- runif(125) 
microbenchmark( mean(x) )  

Which would exercise the surrounded code 125 times (100 by default) and output profiling information such as:

Unit: nanoseconds
    expr  min     lq    mean median     uq   max neval
 sqrt(x)  825  860.5 1212.79  892.5  938.5 12905   100
   x^0.5 3015 3059.5 3776.81 3101.5 3208.0 15215   100   

Where we are concerned with the mean as a good indication of how long each iteration is taking. We should also notice where there is a large divergence from the mean with very distant min and max values—which is what we have here.