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
$X \equiv u$ 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.
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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