Package: dust 0.15.3

Rich FitzJohn

dust: Iterate Multiple Realisations of Stochastic Models

An Engine for simulation of stochastic models. Includes support for running stochastic models in parallel, either with shared or varying parameters. Simulations are run efficiently in compiled code and can be run with a fraction of simulated states returned to R, allowing control over memory usage. Support is provided for building bootstrap particle filter for performing Sequential Monte Carlo (e.g., Gordon et al. 1993 <doi:10.1049/ip-f-2.1993.0015>). The core of the simulation engine is the 'xoshiro256**' algorithm (Blackman and Vigna <arxiv:1805.01407>), and the package is further described in FitzJohn et al 2021 <doi:10.12688/wellcomeopenres.16466.2>.

Authors:Rich FitzJohn [aut, cre], Alex Hill [aut], John Lees [aut], Imperial College of Science, Technology and Medicine [cph]

dust_0.15.3.tar.gz
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dust_0.15.3.tgz(r-4.6-x86_64)dust_0.15.3.tgz(r-4.6-arm64)dust_0.15.3.tgz(r-4.5-x86_64)dust_0.15.3.tgz(r-4.5-arm64)
dust_0.15.3.tar.gz(r-4.7-arm64)dust_0.15.3.tar.gz(r-4.7-x86_64)dust_0.15.3.tar.gz(r-4.6-arm64)dust_0.15.3.tar.gz(r-4.6-x86_64)
dust_0.15.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
dust/json (API)
NEWS

# Install 'dust' in R:
install.packages('dust', repos = c('https://mrc-ide.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mrc-ide/dust/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

cppopenmp

7.76 score 20 stars 4 packages 59 scripts 15 exports 15 dependencies

Last updated from:c135a2fa92 (on master). Checks:2 ERROR, 9 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64ERROR271
linux-devel-x86_64NOTE233
source / vignettesOK305
linux-release-arm64ERROR277
linux-release-x86_64NOTE269
macos-release-arm64NOTE198
macos-release-x86_64NOTE577
macos-oldrel-arm64NOTE152
macos-oldrel-x86_64NOTE491
windows-develNOTE327
windows-releaseNOTE276
windows-oldrelNOTE276
wasm-releaseOK153

Exports:dustdust_cuda_configurationdust_cuda_optionsdust_datadust_exampledust_generatedust_ode_controldust_openmp_supportdust_openmp_threadsdust_packagedust_repair_environmentdust_rngdust_rng_distributed_pointerdust_rng_distributed_statedust_rng_pointer

Dependencies:callrclicpp11descfsgluelifecyclepkgbuildpkgloadprocessxpsR6rlangrprojrootwithr

Algorithms used to compute random numbers

Rendered fromrng_algorithms.Rmdusingknitr::rmarkdownon May 13 2026.

Last update: 2021-11-16
Started: 2021-11-16

Comparing models and data

Rendered fromdata.Rmdusingknitr::rmarkdownon May 13 2026.

Last update: 2023-06-28
Started: 2021-08-25

Distributed parallel random numbers

Rendered fromrng_distributed.Rmdusingknitr::rmarkdownon May 13 2026.

Last update: 2022-11-08
Started: 2021-11-17

Introduction to dust

Rendered fromdust.Rmdusingknitr::rmarkdownon May 13 2026.

Last update: 2023-04-27
Started: 2020-07-06

Multiple parameter sets

Rendered frommulti.Rmdusingknitr::rmarkdownon May 13 2026.

Last update: 2021-10-20
Started: 2021-02-24

Principles and design of dust

Rendered fromdesign.Rmdusingknitr::rmarkdownon May 13 2026.

Last update: 2023-03-17
Started: 2021-02-25

Random number generation

Rendered fromrng.Rmdusingknitr::rmarkdownon May 13 2026.

Last update: 2022-11-02
Started: 2020-07-06

Running models on GPUs with CUDA

Rendered fromgpu.Rmdusingknitr::rmarkdownon May 13 2026.

Last update: 2022-11-08
Started: 2021-11-08

Using RNGs from packages

Rendered fromrng_package.Rmdusingknitr::rmarkdownon May 13 2026.

Last update: 2023-04-27
Started: 2021-11-12