# R Inferno-ism: order is not rank

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Do not use `order`

when you want `rank`

.

## Background

The update of “A comparison of some heuristic optimization methods” is due to the bug that Luca Scrucca spotted.

Actually, it is two bugs:

- I used
`order`

when I meant`rank`

- This somehow escaped being in
*The R Inferno*

## Problem

What I said in my code was (essentially):

ord <- order(x)

Now what I wanted was the order of the values in x. What I got was the permutation of indices that would put x into sorted order. Only under the rarest of circumstances are these the same. But they sound oh so similar.

What I really wanted to say was:

ord <- rank(x, ties.method="first")

(But see below.)

## Timing

Using `order`

in this case doesn’t get us where we want to go. The advantage is that it gets us there really fast. The `rank`

function is much slower. (Timings in R version 2.15.0.)

> x10 <- runif(10) > system.time(for(i in 1:1e4) order(x10)) user system elapsed 0.11 0.00 0.11 > system.time(for(i in 1:1e4) rank(x10, ties.method="first")) user system elapsed 1.22 0.00 1.34 > x100 <- runif(100) > system.time(for(i in 1:1e4) order(x100)) user system elapsed 0.14 0.00 0.17 > system.time(for(i in 1:1e4) rank(x100, ties.method="first")) user system elapsed 1.61 0.00 1.64 > x1000 <- runif(1000) > system.time(for(i in 1:1e4) order(x1000)) user system elapsed 1.14 0.02 1.15 > system.time(for(i in 1:1e4) rank(x1000, ties.method="first")) user system elapsed 3.76 0.00 3.82

`rank`

is clearly slower than `order`

. The whole point, though, is that these two commands give us different things. The command `order(order(x))`

is another way to get what our `rank`

command gives us. Even though it is a bit kludgy, it can be significantly faster:

> system.time(for(i in 1:1e4) rank(x10, ties.method="first")) user system elapsed 1.39 0.00 1.39 > system.time(for(i in 1:1e4) order(order(x10))) user system elapsed 0.23 0.00 0.24 > system.time(for(i in 1:1e4) rank(x100, ties.method="first")) user system elapsed 1.56 0.00 1.56 > system.time(for(i in 1:1e4) order(order(x100))) user system elapsed 0.36 0.00 0.38 > system.time(for(i in 1:1e4) rank(x1000, ties.method="first")) user system elapsed 3.94 0.00 4.00 > system.time(for(i in 1:1e4) order(order(x1000))) user system elapsed 2.17 0.00 2.17 > x10000 <- runif(10000) > system.time(for(i in 1:1e4) rank(x10000, ties.method="first")) user system elapsed 34.88 0.00 35.01 > system.time(for(i in 1:1e4) order(order(x10000))) user system elapsed 29.51 0.00 29.94

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