NEWS.md
dqrng::rng64_t
type has been changed to use Rcpp::XPtr
instead of std::shared_ptr
and the functions from dqrng_sample.h
now expect a reference to dqrng::random_64bit_generator
instead of dqrng::rng64_t
(#70 fixing #63)LinkingTo: sitmo
.xoshiro.h
dqrng.register_methods
is set to TRUE
.dqrng_types.h
(#75 together with Paul Liétar)random_64bit_generator
with additional convenience methods (fixing #64 in #79)
clone(stream)
method to allow using the global RNG state for parallel computation. Note that for consistency with the other provided RNGs, stream
is counted relative to the current stream for PCG64.variate<dist>(param)
, generate<dist>(container, param)
etc. using and inspired by randutils
.dqrng::runif
, dqrng::rnorm
and dqrng::rexp
available from dqrng.h
have been deprecated and will be removed in a future release. Please use the more flexible and faster dqrng::random_64bit_accessor
together with variate<Dist>()
instead. The same applies to dqrng::uniform01
from dqrng_distribution.h
, which can be replaced by the member function dqrng::random_64bit_generator::uniform01
.dqrng::extra::parallel_generate
in dqrng_extra/parallel_generate.h
as an example for using the global RNG in a parallel context (fixing #77 in #82 together with Philippe Grosjean)dqrrademacher
for drawing Rademacher weights (Kyle Butts in #50 fixing #49)dqrmvnorm
sampling from a multivariate normal distribution. This uses the methods implemented in the mvtnorm
package and uses dqrnorm
.long_jump()
for Xo(ro)shiro as alternative to jump()
providing fewer streams with longer period.dqsample
and dqsample.int
using an unbiased sampling algorithm.R_unif_index()
instead of unif_rand()
to retrieve random data from R’s RNG in generateSeedVectors()
.int
is used for seeding (Aaron Lun in #10)
dqrng::dqset_seed()
expects a Rcpp::IntegerVector
instead of an int
generateSeedVectors()
for generating a list of random int
vectors from R’s RNG. These vectors can be used as seed (Aaron Lun in #10).std::random_device
as source of the default seed, since std::random_device
is deterministic with MinGW (c.f. #2)