Prints type of unuran
generator, data used from distribution,
parameter for algorithm, performance characteristic, and hints to
adjust the performance of the generator.
It also returns a list that contains some of these data.
[Advanced] -- Print object.
unuran.details(unr, show=TRUE, return.list=FALSE, debug=FALSE)
an unuran
object.
whether the data are printed on the console. (boolean)
whether some of the data are returned in a list. (boolean)
if TRUE, store additional data in returned list. This might be useful to examine a method. (boolean)
Josef Leydold and Wolfgang H\"ormann unuran@statmath.wu.ac.at.
If show
is TRUE
then this routine prints data about the
generator object to the console.
If return.list
is TRUE
then a list that contains some of
these data is returned. This is an experimental feature and components of
the list may be extended in future releases.
The components of the returned list depend on the particular method. However, the following are common to all objects:
method
string that contains the name of the generation method.
type
one of the following strings that describes the type of the generation method:
"inv"
inversion method
"ar"
acceptance-rejection method
"iar"
acceptance-rejection whether inversion is used for the proposal distribution
"mcmc"
Markov chain Monte Carlo sampler
"other"
none of the above methods
distr.class
one of the following strings that describes the class of the distribution:
"cont"
univariate continuous distribution
"discr"
univariate discrete distribution
"cont"
multivariate continuous distribution
In addition the following components may be available:
area.pdf
area below density function of the distribution.
area.hat
area below hat function for an acceptance-rejection method.
rejection.constant
rejection constant for an
acceptance-rejection method.
It given as the ratio area.hat / area.pdf
.
area.squeeze
area below squeeze function for an
acceptance-rejection method.
area.hat / area.squeeze
can be used as upper bound for the
rejection constant.
intervals
integer that contains the number of subintervals into which the domain of the target distribution is split for constructing a hat function / approximating function.
truncated.domain
vector of length 2 that contains upper and lower boundary of the ‘computational domain’ that is used for constructing an approximating function.
unuran
.
## Create a generator object
distr <- udnorm()
gen <- tdrd.new(distr)
## print data about object on console
unuran.details(gen)
## get list with some of these data
data <- unuran.details(gen,return.list=TRUE)
Run the code above in your browser using DataLab