| Uniform {stats} | R Documentation |
The Uniform Distribution
Description
Density, distribution function, quantile function and random
generation for the uniform distribution on the interval from
min to max.
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 |
min, max |
lower and upper limits of the distribution. Must be finite. |
log, log.p |
logical; if |
lower.tail |
logical; if |
Details
If min or max are not specified they assume the default
values of 0 and 1 respectively.
The uniform distribution has density
f(x) = \frac{1}{max-min}
for min \le x \le max.
For the case of u := min == max, the limit case of
X \equiv 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.
Value
dunif gives the density,
punif is the cumulative distribution function, and
qunif is the quantile function of the uniform distribution.
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 arguments for the other functions.
The numerical arguments other than n are recycled to the
length of the result. Only the first elements of the logical
arguments are used.
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.
References
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
See Also
RNG about random number generation in R.
Distributions for other standard distributions.
Examples
u <- runif(20)
## The following relations always hold :
punif(u) == u
dunif(u) == 1
var(runif(10000)) #- ~ = 1/12 = .08333