sundialr

sundialr

sundialr is a wrapper around a few of the solvers in the SUNDIALS ODE solving C library produced by the Lawrence Livermore National Laboratory and Southern Methodist University. More information about SUNDIALS can be found here. SUNDIALS is one of the most popular and well-respected ODE solving libraries available and sundialr provides a way to interface some of the SUNDIALS solvers in R.

Currently sundialr provides an interface to the serial versions of cvode (for solving ODES), cvodes (for solving ODE with sensitivity equations) and ida (for solving differential-algebraic equations) using the Linear Solver (dense version).

A convenience function cvsolve is provided which allows solving a system of equations with multiple discontinuities in solution. An application of such a system of equations would be to simulate the effect of multiple bolus doses of a drug in clinical pharmacokinetics. See the vignette for more details.

What’s new?

Comments for version 0.1.6

• Updated the upstream SUNDIALS to version 7.2.0
• Complete overall of the build system to use cmake based installation

Comments for version 0.1.5

• Updated the upstream SUNDIALS to version 7.1.1.
• Fixed the pkgdown website
• There was a bug in assigning absolute tolerance in equations. Fixed now.

Comments for version 0.1.4.1.2

• Fixed the issue with forwarded email address.

Release 0.1.4.1

• Fixed the linking bug due to multiple defined symbols. No other change.

Release 0.1.4

• This version has version 5.2.0 of SUNDIALS (released in March 2020) at the back end.
• A new function cvsolve is added. It allows solving ODEs with multiple discontinuities in the solution. See a complete use case in the vignette.
• A pkgdown create site of the package is added.
• A hex sticker for the package is released!

Release 0.1.3

• This version has version 4.0.1 of SUNDIALS (released in Dec 2018) at the back end.
• An interface to CVODES is added. It calculates forward sensitivities w.r.t all parameters of the ODE system.
• Parameters can now be defined as an input parameter to the ODE function. This will allow performing parameter optimization via numerical optimizers.