I was always slightly crippled due to the lack of accuracy that I see in the table markings with system.time and rbenchmark (since time accuracy may be absent) and saw that Hadley refers to the microbenchmark package, so I decided to give it a whirlwind, as shown below. I pitted mean against f <- function(x) {sum(x)/length(x)} and expected mean to make the path better than f , but the results, as I understand them, do not indicate that this is true.
- Do I really not understand the results?
 - Is f faster than average?
 - Is microbusiness still in beta, and does it need to be ironed outside the home?
 
I run R2.15 on a machine with a win of 7 (since microbenchmark performs timings differently depending on your OS).
results
 Unit: microseconds expr min lq median uq max 1 f(x) 19.130 20.529 20.529 20.996 286.00 2 mean(x) 28.927 29.860 30.327 30.327 672.31 
The code
 library(microbenchmark) x <- 1:10000 f <- function(x) {sum(x)/length(x)} mean(x) res <- microbenchmark( mean(x), f(x), times=1000L) print(res) boxplot(res) 
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