# AllDuplicated

##### Index Vector of All Values Involved in Ties

The function `duplicated`

returns a logical vector indicating which elements x are duplicates, but will not include the very first appearance of subsequently duplicated elements. `AllDuplicated`

returns an index vector of ALL the values in `x`

which are involved in ties.
So `!AllDuplicated`

can be used to determine all elements of x, which
appear exactly once (thus with frequency 1).

- Keywords
- manip

##### Usage

`AllDuplicated(x)`

##### Arguments

- x
- vector of any type.

##### Value

##### See Also

`unique`

returns a unique list of all values in x
`duplicated`

returns an index vector flagging all elements, which appeared more than once (leaving out the first appearance!)
`union`

(A, B) returns a list with the unique values from A and B
`intersect`

returns all elements which appear in A and in B
`setdiff`

(A, B) returns all elements appearing in A but not in B
`setequal`

(A, B) returns `TRUE`

if A contains exactly the same elements as B
`split`

(A, A) returns a list with all the tied values in A (see examples)

##### Examples

```
x <- c(1:10, 4:6)
AllDuplicated(x)
# compare to:
duplicated(x)
x[!AllDuplicated(x)]
# union, intersect and friends...
A <- c(sort(sample(1:20, 9)),NA)
B <- c(sort(sample(3:23, 7)),NA)
# all elements from A and B (no duplicates)
union(A, B)
# all elements appearing in A and in B
intersect(A, B)
# elements in A, but not in B
setdiff(A, B)
# elements in B, but not in A
setdiff(B, A)
# Does A contain the same elements as B?
setequal(A, B)
# Find ties in a vector x
x <- sample(letters[1:10], 20, replace=TRUE)
ties <- split(x, x)
# count tied groups
sum(sapply(ties, length) > 1)
# length of tied groups
(x <- sapply(ties, length))[x>1]
# by means of table
tab <- table(x)
tab[tab>1]
# count elements involved in ties
sum(tab>1)
# count tied groups
sum(tab[tab>1])
```

*Documentation reproduced from package DescTools, version 0.99.19, License: GPL (>= 2)*