Specialized alternative to rdo()
or rfun()
for creating rvar
s from
existing random-number generator functions (such as rnorm()
, rbinom()
, etc).
rvar_rng(.f, n, ..., ndraws = NULL)
A single-dimensional rvar
of length n
.
(function) A function (or string naming a function) representing a
random-number generating function that follows the pattern of base random
number generators (like rnorm()
, rbinom()
, etc). It must:
Have a first argument, n
, giving the number of draws to take from the
distribution
Have vectorized parameter arguments
Return a single vector of length n
(positive integer) The length of the output rvar
vector (not
the number of draws).
Arguments passed to .f
. These arguments may include rvar
s,
so long as they are vectors only (no multidimensional rvar
s are
allowed).
(positive integer) The number of draws used to construct the
returned random variable if no rvar
s are supplied in ...
. If NULL
,
getOption("posterior.rvar_ndraws")
is used (default 4000). If ...
contains rvar
s, the number of draws in the provided rvar
s is used
instead of the value of this argument.
This function unwraps the arrays underlying the input rvar
s in
...
and then passes them to .f
, relying on the vectorization of .f
to evaluate it across draws from the input rvar
s. This is why the arguments
of .f
must be vectorized. It asks for n
times the number of draws
in the input rvar
s (or ndraws
if none are given) draws from the
random number generator .f
, then reshapes the output from .f
into an
rvar
with length n
.
rvar_rng()
is a fast alternative to rdo()
or rfun()
, but you must
ensure that .f
satisfies the preconditions described above for the result
to be correct. Most base random number generators satisfy these conditions.
It is advisable to test against rdo()
or rfun()
(which should be correct,
but slower) if you are uncertain.
Other rfun:
rdo()
,
rfun()
mu <- rvar_rng(rnorm, 10, mean = 1:10, sd = 1)
sigma <- rvar_rng(rgamma, 1, shape = 1, rate = 1)
x <- rvar_rng(rnorm, 10, mu, sigma)
x
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