# Uniform {stats}

### Description

These functions provide information about the uniform distribution on the interval from `min`

to `max`

. `dunif`

gives the density, `punif`

gives the distribution function `qunif`

gives the quantile function and `runif`

generates random deviates.

### Usage

dunif(x, min = 0, max = 1, log = FALSE) punif(q, min = 0, max = 1, lower.tail = TRUE, log.p = FALSE) qunif(p, min = 0, max = 1, lower.tail = TRUE, log.p = FALSE) runif(n, min = 0, max = 1)

### Arguments

- x, q
- vector of quantiles.
- p
- vector of probabilities.
- n
- number of observations. If
`length(n) > 1`

, the length is taken to be the number required. - min, max
- lower and upper limits of the distribution. Must be finite.
- log, log.p
- logical; if TRUE, probabilities p are given as log(p).
- lower.tail
- logical; if TRUE (default), probabilities are P[X ≤ x], otherwise, P[X > x].

### Details

If `min`

or `max`

are not specified they assume the default values of ` `

and `1`

respectively.

The uniform distribution has density f(x) = 1/(max-min) for min ≤ x ≤ max.

For the case of u := min == max, the limit case of X == u is assumed, although there is no density in that case and `dunif`

will return `NaN`

(the error condition).

`runif`

will not generate either of the extreme values unless `max = min`

or `max-min`

is small compared to `min`

, and in particular not for the default arguments.

### Values

`dunif`

gives the density, `punif`

gives the distribution function, `qunif`

gives the quantile function, and `runif`

generates random deviates. The length of the result is determined by `n`

for `runif`

, and is the maximum of the lengths of the numerical parameters for the other functions. The numerical parameters other than `n`

are recycled to the length of the result. Only the first elements of the logical parameters are used.

### References

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

### Note

The characteristics of output from pseudo-random number generators (such as precision and periodicity) vary widely. See `.Random.seed`

for more information on R's random number generation algorithms.

### See Also

`RNG`

about random number generation in R.

Distributions for other standard distributions.

### Examples

Documentation reproduced from R 3.0.2. License: GPL-2.