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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "diffeqr" in publications use:'
type: software
license: MIT
title: 'diffeqr: Solving Differential Equations (ODEs, SDEs, DDEs, DAEs)'
version: 2.1.0
doi: 10.5334/jors.151
identifiers:
- type: doi
  value: 10.32614/CRAN.package.diffeqr
abstract: An interface to 'DifferentialEquations.jl' <https://diffeq.sciml.ai/dev/>
  from the R programming language. It has unique high performance methods for solving
  ordinary differential equations (ODE), stochastic differential equations (SDE),
  delay differential equations (DDE), differential-algebraic equations (DAE), and
  more. Much of the functionality, including features like adaptive time stepping
  in SDEs, are unique and allow for multiple orders of magnitude speedup over more
  common methods. Supports GPUs, with support for CUDA (NVIDIA), AMD GPUs, Intel oneAPI
  GPUs, and Apple's Metal (M-series chip GPUs). 'diffeqr' attaches an R interface
  onto the package, allowing seamless use of this tooling by R users. For more information,
  see Rackauckas and Nie (2017) <https://doi.org/10.5334/jors.151>.
authors:
- family-names: Rackauckas
  given-names: Christopher
  email: me@chrisrackauckas.com
preferred-citation:
  type: article
  title: DifferentialEquations.jl – A Performant and Feature-Rich Ecosystem for Solving
    Differential Equations in Julia
  authors:
  - family-names: Rackauckas
    given-names: Chris
  - family-names: Nie
    given-names: Qing
  doi: 10.5334/jors.151
  journal: The Journal of Open Source Software
  year: '2017'
  volume: '5'
  issue: '1'
  url: https://openresearchsoftware.metajnl.com/articles/10.5334/jors.151/
  notes: R package version 2.1.0
repository: https://CRAN.R-project.org/package=diffeqr
repository-code: https://github.com/SciML/diffeqr
url: https://github.com/SciML/diffeqr
date-released: '2024-12-04'
contact:
- family-names: Rackauckas
  given-names: Christopher
  email: me@chrisrackauckas.com