min to max. dunif gives the
density, punif gives the distribution function qunif
gives the quantile function and runif generates random
deviates.
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)length(n) > 1, the length
is taken to be the number required.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 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.
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
$X == u$ 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.
RNG about random number generation in R.Distributions for other standard distributions.
u <- runif(20)
## The following relations always hold :
punif(u) == u
dunif(u) == 1
var(runif(10000)) #- ~ = 1/12 = .08333
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