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.
show: whether the data are printed on the console. (boolean)
return.list: whether some of the data are returned in a list. (boolean)
debug: if TRUE, store additional data in returned list. This might be useful to examine a method. (boolean)
Details
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.
## Create a generator objectdistr <- udnorm()gen <- tdrd.new(distr)## print data about object on consoleunuran.details(gen)## get list with some of these datadata <- unuran.details(gen,return.list=TRUE)