Uniform
The Uniform Distribution

### Description

Calculates density, cumulative probability, quantile, and generates a random sample for the uniform distribution (continuous).

### Usage

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

### Arguments

x, q | numeric vectors in the range [min, max] that specify the quantiles.
p | a numeric vector in the range [0, 1] that specifies the probabilities.
n | an integer in the range [0, Inf) that specifies the number of random samples requested. If the input value is not an integer, it is truncated. If length(n) is greater than 1, the random function returns length(n) random samples.
min | a numeric vector in the range (-Inf, Inf) that specifies lower limits. In the case of runif, min to max is an open interval unless min = max. That is, if min = 0 and max = 1, then no random numbers will ever be exactly 0 or 1.
max | a numeric vector in the range (-Inf, Inf) that specifies upper limits, which are greater than or equal to lower limits specified in min. In the case of runif, min to max is an open interval unless min = max. That is, if min = 0 and max = 1, then no random numbers will ever be exactly 0 or 1.
log | a logical value. If FALSE (default), the density function returns the density itself. If TRUE, it returns the log of the density.
lower.tail | a logical value. If TRUE (default), the probability supplied to the quantile function or returned by the probability function is P[X <= x]. If FALSE, it is P[X > x].
log.p | a logical value. If FALSE (default), the probability supplied to the quantile function or returned by the probability function is the probability itself. If TRUE, it is the log of the probability.

### Details

The distribution parameter(s) are replicated cyclically to be the same length as the input x, q, p, or the number of random samples requested.
Missing values (NAs) in the input or the distribution parameter(s) will cause the corresponding elements of the result to be missing.
Value
returns returns density (dunif), cumulative probability (punif), quantile (qunif), or random sample (runif) for the uniform distribution with parameters min and max.
Side Effects
If the .Random.seed dataset exists, the random sample function updates its value. The random sample function creates the .Random.seed dataset if it does not exist.
Background
The uniform distribution is a family of continuous probability distributions defined on the interval [min, max] and parameterized by two parameters, min and max.
The uniform (or rectangular) distribution takes values equally likely from min to max. The uniform distribution has several uses but it is commonly used to model round-off errors.
References
Johnson, N. L. and Kotz, S. (1970). Continuous Univariate Distributions, vol. 2. Houghton-Mifflin, Boston.
Differences between Spotfire Enterprise Runtime for R and Open-source R

- In open-source R, min = max is allowed for {p,q,r}unif but dunif(2, 2, 2) returns NaN and generates a warning.
- In Spotfire Enterprise Runtime for R, min = max is allowed for all {d,p,q,r}unif and dunif(2, 2, 2) returns Inf.

See Also
set.seed, To generate a uniform sample on integers or populations use sample.
Examples

    x <- 1:10
    x + runif(x)   # jitter the x data $
    runif(100, -1, 1) # 100 numbers uniform on -1 to 1

Package stats version 6.1.5-18
Package Index