c(person("Beilun", "Wang", role = c("aut", "cre"), email = "bw4mw@virginia.edu"), person("Yanjun", "Qi", role = "aut", email = "yanjun@virginia.edu"),person("Zhaoyang", "Wang", role = c("aut"), email = "zw4dn@virginia.edu"))
Beilun Wang [aut, cre],
Yanjun Qi [aut],
Zhaoyang Wang [aut]

Solving Differential Equations (ODEs, SDEs, DDEs, DAEs)
person("Christopher", "Rackauckas", email = "me@chrisrackauckas.com", role = c("aut", "cre"))
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.
'diffeqr' attaches an R interface onto the package, allowing seamless use of this tooling by R users.

An interface to 'DifferentialEquations.jl' <http://docs.juliadiffeq.org/latest/> 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.
'diffeqr' attaches an R interface onto the package, allowing seamless use of this tooling by R users.

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.
'diffeqr' attaches an R interface onto the package, allowing seamless use of this tooling by R users.
Julia (>= 1.5), DifferentialEquations.jl,
ModelingToolkit.jl