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)