getRNG returns the Random Number Generator (RNG)
settings used for computing an object, using a suitable
.getRNG S4 method to extract these settings. For
example, in the case of objects that result from multiple
model fits, it would return the RNG settings used to
compute the best fit.
hasRNG tells if an object has embedded RNG data.
.getRNG is an S4 generic that extract RNG settings
from a variety of object types. Its methods define the
workhorse functions that are called by getRNG.
getRNG1 is defined to provide separate access to
the RNG settings as they were at the very beginning of a
whole computation, which might differ from the RNG
settings returned by getRNG, that allows to
reproduce the result only.
nextRNG returns the RNG settings as they would be
after seeding with object.
setRNG set the current RNG with a seed, using a
suitable .setRNG method to set these settings.
.setRNG is an S4 generic that sets the current RNG
settings, from a variety of specifications. Its methods
define the workhorse functions that are called by
setRNG.
getRNG(object, ..., num.ok = FALSE, extract = TRUE, recursive = TRUE) hasRNG(object) .getRNG(object, ...) getRNG1(object, ...) nextRNG(object, ..., ndraw = 0L) setRNG(object, ..., verbose = FALSE, check = TRUE) .setRNG(object, ...)
.Random.seed or embedded RNG data, e.g.,
in S3/S4 slot rng or rng$noise..getRNG or
.setRNG.TRUE) or passed to
set.seed into a proper RNG seed
(FALSE) (See details and examples).TRUE) or
if the object itself should be considered as an RNG
specification.TRUE) or
only once (FASE).getRNG, getRNG1, nextRNG and
setRNG usually return an integer vector of length
> 2L, like .Random.seed.
getRNG and getRNG1 return NULL if no
RNG data was found.
setRNG invisibly returns the old RNG settings as
they were before changing them.
This function handles single number RNG specifications in the following way:
RNG). No validity check
is performed. num.ok=TRUE
return them unchanged. Otherwise, consider them as
(pre-)seeds and pass them to set.seed to
get a proper RNG seed. Hence calling getRNG(1234)
is equivalent to set.seed(1234); getRNG() (See
examples). Think of a sequence of separate computations, from which
only one result is used for the result (e.g. the one that
maximises a likelihood): getRNG1 would return the
RNG settings to reproduce the complete sequence of
computations, while getRNG would return the RNG
settings necessary to reproduce only the computation
whose result has maximum likelihood.
signature(object = "ANY"): Default
method that tries to extract RNG information from
object, by looking sequentially to a slot named
'rng', a slot named 'rng.seed' or an
attribute names 'rng'.
It returns NULL if no RNG data was found.
signature(object = "missing"):
Returns the current RNG settings.
signature(object = "list"): Method
for S3 objects, that aims at reproducing the behaviour of
the function getRNG of the package getRNG.
It sequentially looks for RNG data in elements
'rng', noise$rng if element 'noise'
exists and is a list, or in attribute
'rng'.
signature(object = "numeric"):
Method for numeric vectors, which returns the object
itself, coerced into an integer vector if necessary, as
it is assumed to already represent a value for
.Random.seed.
signature(object = "ANY"): Default
method that is identical to getRNG(object, ...).
signature(object = "character"):
Sets the RNG to kind object, assuming is a valid
RNG kind: it is equivalent to RNGkind(object, ....
All arguments in ... are passed to
RNGkind.
signature(object = "numeric"): Sets
the RNG settings using object directly the new
value for .Random.seed or to initialise it with
set.seed.