Generic function for drawing random samples from distribution objects.
random(x, n = 1L, drop = TRUE, ...)# S3 method for distribution
simulate(object, nsim = 1L, seed = NULL, ...)
Random samples drawn from the distriubtion x
. The random
methods typically return either a matrix or, if possible, a vector. The
simulate
method always returns a data frame (with an attribute
"seed"
containing the .Random.seed
from before the simulation).
An object. The package provides methods for distribution
objects such as those from Normal()
or Binomial()
etc.
The number of samples to draw. Should be a positive
integer. Defaults to 1L
.
logical. Should the result be simplified to a vector if possible?
Arguments passed to methods. Unevaluated arguments will generate a warning to catch mispellings or other possible errors.
An optional random seed that is to be set using set.seed
prior to drawing the random sample. The previous random seed from the global
environment (if any) is restored afterwards.
random
is a new generic for drawing random samples from
the S3 distribution
objects provided in this package, such as
Normal
or Binomial
etc. The respective
methods typically call the "r" function for the corresponding
distribution functions provided in base R such as rnorm
,
rbinom
etc.
In addition to the new random
generic there is also a
simulate
method for distribution objects which simply
calls the random
method internally.
## distribution object
X <- Normal()
## 10 random samples
random(X, 10)
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