ida: SUNDIALS IDA Solver for Differential-Algebraic Equation...
In Rsundials: Suite of Nonlinear Differential Algebraic Equations Solvers in R

Description Usage Arguments Examples

This function allows for evaluation of DAE systems using the SUNDIALS IDA solver hard coded in C.

 
	ida(y, yp, times, package, resfunc, jacfunc = NULL, rootfunc = NULL, fndata = NULL,
		numroots = 0, rtol = 1e-6, atol = 1e-6, maxnumsteps = 500, maxstep = 0, verbose = FALSE, 
		lasttime = FALSE)

`y`	a numeric vector of the initial values of y of the DAE system.
`yp`	a numeric vector of the initial values of y' of the DAE system.
`times`	a numeric vector of times at which explicit estimates for y are desired. The first element should be the initial time (often 0). The IDA solver takes steps until the next requested time step t is overtaken. It then computes y(t) by interpolation. To easily create geometric sequences, the function gseq can be used.
`package`	a character vector of the package name containing the user-defined residual function. If the residual function is contained within the file "usrfcns.c" for example, the command R CMD SHLIB usrfcns.c will create the package "usrfcns" which can be loaded using the command dyn.load("usrfcns.so") or dyn.load("usrfcns.dll") depending on your system.
`resfunc`	a character vector defining name of the user-defined residual function contained within the package specified by the `package` variable. This need not match the name of the package itself.
`jacfunc`	a character vector defining the name of the user-defined Jacobian (if desired). By default, the IDA solver will approximate the Jacobian by difference quotients.
`rootfunc`	a character vector defining the name of the user-defined method (in C) for computing the roots of some set of functions. The number of functions is set by /codenumroots.
`fndata`	a numeric vector of data to be used by the user-defined functions.
`numroots`	the number of functions defined by rootfunc.
`rtol`	a scalar that defines the relative error tolerance. The relative error tolerance is not recommended to exceed 1.0E-3. On the other hand, `reltol` should not be so small that it is comparable to the unit roundoff of the machine arithmetic (generally around 1.0E-15).
`atol`	a scalar or vector that defines the absolute error tolerance(s). The absolute tolerances need to be set to control absolute errors when any components of the solution vector `y` may be so small that pure relative error control is meaningless.
`maxnumsteps`	a scalar that sets the maximum number of steps per timestep. The default is 500.
`maxstep`	a scalar that sets the maximum absolute step size. The default is 0 = infinity.
`verbose`	a logical value that, when TRUE, triggers verbose output from the solver.
`lasttime`	by default, with lasttime = FALSE, a data frame is returned that includes all of the values y at each time point. If lasttime is set to TRUE, only the last values of y will be returned (i.e. at the last time point specified).