# combn

##### Generate All Combinations of n Elements, Taken m at a Time

Generate all combinations of the elements of `x`

taken `m`

at a time. If `x`

is a positive integer, returns all
combinations of the elements of `seq(x)`

taken `m`

at a
time. If argument `FUN`

is not `NULL`

, applies a function given
by the argument to each point. If simplify is FALSE, returns
a list; otherwise returns an `array`

, typically a
`matrix`

. `...`

are passed unchanged to the
`FUN`

function, if specified.

##### Usage

`combn(x, m, FUN = NULL, simplify = TRUE, …)`

##### Arguments

- x
vector source for combinations, or integer

`n`

for`x <- seq_len(n)`

.- m
number of elements to choose.

- FUN
function to be applied to each combination; default

`NULL`

means the identity, i.e., to return the combination (vector of length`m`

).- simplify
logical indicating if the result should be simplified to an

`array`

(typically a`matrix`

); if FALSE, the function returns a`list`

. Note that when`simplify = TRUE`

as by default, the dimension of the result is simply determined from`FUN(`

(for efficiency reasons). This will badly fail if`1st combination`)`FUN(u)`

is not of constant length.- …
optionally, further arguments to

`FUN`

.

##### Details

Factors `x`

are accepted.

##### Value

A `list`

or `array`

, see the `simplify`

argument above. In the latter case, the identity
`dim(combn(n, m)) == c(m, choose(n, m))`

holds.

##### References

Nijenhuis, A. and Wilf, H.S. (1978)
*Combinatorial Algorithms for Computers and Calculators*;
Academic Press, NY.

##### See Also

`choose`

for fast computation of the *number* of
combinations. `expand.grid`

for creating a data frame from
all combinations of factors or vectors.

##### Examples

`library(utils)`

```
combn(letters[1:4], 2)
(m <- combn(10, 5, min)) # minimum value in each combination
mm <- combn(15, 6, function(x) matrix(x, 2, 3))
stopifnot(round(choose(10, 5)) == length(m),
c(2,3, round(choose(15, 6))) == dim(mm))
## Different way of encoding points:
combn(c(1,1,1,1,2,2,2,3,3,4), 3, tabulate, nbins = 4)
## Compute support points and (scaled) probabilities for a
## Multivariate-Hypergeometric(n = 3, N = c(4,3,2,1)) p.f.:
# table.mat(t(combn(c(1,1,1,1,2,2,2,3,3,4), 3, tabulate, nbins = 4)))
## Assuring the identity
for(n in 1:7)
for(m in 0:n) stopifnot(is.array(cc <- combn(n, m)),
dim(cc) == c(m, choose(n, m)))
```

*Documentation reproduced from package utils, version 3.4.1, License: Part of R 3.4.1*