# quantile

##### Sample Quantiles

The generic function `quantile`

produces sample quantiles
corresponding to the given probabilities.
The smallest observation corresponds to a probability of 0 and the
largest to a probability of 1.

- Keywords
- univar

##### Usage

`quantile(x, ...)`## S3 method for class 'default':
quantile(x, probs = seq(0, 1, 0.25), na.rm = FALSE,
names = TRUE, type = 7, ...)

##### Arguments

- x
- numeric vector whose sample quantiles are wanted, or an
object of a class for which a method has been defined (see also
details ).`NA`

and`NaN`

values are not allowed in numeric vectors unless`na.rm`

is`TRUE`

. - probs
- numeric vector of probabilities with values in
$[0,1]$. (Values up to
`2e-14`outside that range are accepted and moved to the nearby endpoint.) - na.rm
- logical; if true, any
`NA`

and`NaN`

's are removed from`x`

before the quantiles are computed. - names
- logical; if true, the result has a
`names`

attribute. Set to`FALSE`

for speedup with many`probs`

. - type
- an integer between 1 and 9 selecting one of the nine quantile algorithms detailed below to be used.
- ...
- further arguments passed to or from other methods.

##### Details

A vector of length `length(probs)`

is returned;
if `names = TRUE`

, it has a `names`

attribute.

`NA`

and `NaN`

values in `probs`

are
propagated to the result.

The default method works with classed objects sufficiently like
numeric vectors that `sort`

and (not needed by types 1 and 3)
addition of elements and multiplication by a number work correctly.
Note that as this is in a namespace, the copy of `sort`

in
`quantile`

can be applied to complex vectors which (apart
from ties) will be ordered on their real parts.

There is a method for the date-time classes (see
`"POSIXt"`

). Types 1 and 3 can be used for class
`"Date"`

and for ordered factors.

##### References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988)
*The New S Language*.
Wadsworth & Brooks/Cole.

Hyndman, R. J. and Fan, Y. (1996) Sample quantiles in statistical
packages, *American Statistician* **50**, 361--365.

##### See Also

`ecdf`

for empirical distributions of which
`quantile`

is an inverse;
`boxplot.stats`

and `fivenum`

for computing
other versions of quartiles, etc.

##### Examples

`library(stats)`

```
quantile(x <- rnorm(1001)) # Extremes & Quartiles by default
quantile(x, probs = c(0.1, 0.5, 1, 2, 5, 10, 50, NA)/100)
### Compare different types
p <- c(0.1, 0.5, 1, 2, 5, 10, 50)/100
res <- matrix(as.numeric(NA), 9, 7)
for(type in 1:9) res[type, ] <- y <- quantile(x, p, type = type)
dimnames(res) <- list(1:9, names(y))
round(res, 3)
```

*Documentation reproduced from package stats, version 3.3, License: Part of R 3.3*