Extremes {base} R Documentation

## Maxima and Minima

### Description

Returns the (parallel) maxima and minima of the input values.

### Usage

```max(..., na.rm=FALSE)
min(..., na.rm=FALSE)

pmax(..., na.rm=FALSE)
pmin(..., na.rm=FALSE)
```

### Arguments

 `...` numeric arguments. `na.rm` a logical indicating whether missing values should be removed.

### Value

`max` and `min` return the maximum or minimum of all the values present in their arguments, as `integer` if all are `integer`, or as `double` otherwise.
The minimum and maximum of an empty set are `+Inf` and `-Inf` (in this order!) which ensures transitivity, e.g., `min(x1, min(x2)) == min(x1,x2)`. In R versions before 1.5, `min(integer(0)) == .Machine\$integer.max`, and analogously for `max`, preserving argument type, whereas from R version 1.5.0, `max(x) == -Inf` and `min(x) == +Inf` whenever `length(x) == 0` (after removing missing values if requested).
If `na.rm` is `FALSE` an `NA` value in any of the arguments will cause a value of `NA` to be returned, otherwise `NA` values are ignored.
`pmax` and `pmin` take several vectors (or matrices) as arguments and return a single vector giving the parallel maxima (or minima) of the vectors. The first element of the result is the maximum (minimum) of the first elements of all the arguments, the second element of the result is the maximum (minimum) of the second elements of all the arguments and so on. Shorter vectors are recycled if necessary. If `na.rm` is `FALSE`, `NA` values in the input vectors will produce `NA` values in the output. If `na.rm` is `TRUE`, `NA` values are ignored. `attributes` (such as `names` or `dim`) are transferred from the first argument (if applicable).
`max` and `min` are generic functions: methods can be defined for them individually or via the `Summary` group generic.

### References

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

`range` (both min and max) and `which.min` (`which.max`) for the arg min, i.e., the location where an extreme value occurs.

### Examples

```require(stats)
min(5:1,pi)
pmin(5:1, pi)
x <- sort(rnorm(100));  cH <- 1.35
pmin(cH, quantile(x)) # no names
pmin(quantile(x), cH) # has names
plot(x, pmin(cH, pmax(-cH, x)), type='b', main= "Huber's function")
```

[Package base version 2.1.0 Index]