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diffeqr
View on CRAN: Click
here
Download and install diffeqr package within the R console
Install from CRAN:
install.packages("diffeqr")
Install from Github:
library("remotes")
install_github("cran/diffeqr")
Install by package version:
library("remotes")
install_version("diffeqr", "2.0.1")
Attach the package and use:
library("diffeqr")
Maintained by
Christopher Rackauckas
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-04-24
Latest Update: 2023-10-20
Description:
An interface to 'DifferentialEquations.jl' 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) .
How to cite:
Christopher Rackauckas (2018). diffeqr: Solving Differential Equations (ODEs, SDEs, DDEs, DAEs). R package version 2.0.1, https://cran.r-project.org/web/packages/diffeqr. Accessed 21 Nov. 2024.
Previous versions and publish date:
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Other R packages that diffeqr depends,
imports, suggests or enhances
Complete documentation for diffeqr
Functions, R codes and Examples using
the diffeqr R package
Some associated functions: diffeq_setup . diffeqgpu_setup . jitoptimize_ode . jitoptimize_sde .
Some associated R codes: diffeqr.R . Full diffeqr package functions and examples
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