rkMethod {deSolve} | R Documentation |
This function returns a list specifying coefficients and properties of ODE solver methods from the Runge-Kutta family.
rkMethod(method = NULL, ...)
method |
a string constant naming one of the pre-defined methods
of the Runge-Kutta family of solvers. The most common methods are
the fixed-step methods "euler" , "rk2" , "rk4" or
the variable step methods "rk23bs" (alias "ode23" ) or
"rk45dp7" (alias "ode45" ).
|
... |
specification of a user-defined solver, see Value and example below. |
This function supplies method
settings for rk
or
ode
. If called without arguments, the names of all
implemented solvers of the Runge-Kutta family are returned.
The following comparison gives an idea how the algorithms of deSolve are related to similar algorithms of other simulation languages:
rkMethod | | | Description |
"euler" | | | Euler's Method |
"rk2" | | | 2nd order Runge-Kutta, fixed time step (Heun's method) |
"rk4" | | | classical 4th order Runge-Kutta, fixed time step |
"rk23" | | | Runge-Kutta, order 2(3), Octave: ode23 |
"rk23bs", "ode23" | | | Bogacki-Shampine, order 2(3), Matlab: ode23 |
"rk34f" | | | Runge-Kutta-Fehlberg, order 3(4) |
"rk45f" | | | Runge-Kutta-Fehlberg, order 4(5), Octave: ode45, pair=1 |
"rk45e" | | | Runge-Kutta-England, order 4(5) |
"rk45dp6" | | | Dormand-Prince, order 4(5), local order 6 |
"rk45dp7", "ode45" | | | Dormand-Prince 4(5), local order 7 |
| | (also known as dopri5, MATLAB: ode45, Octave: ode45, pair=0) |
Note that this table is based on the Runge-Kutta coefficients only, but the algorithms differ also in their implementation, in their stepsize adaption strategy and interpolation methods. The table reflects the state at time of writing and it is of course possible that implementations change.
A list with the following elements:
ID |
name of the method (character) |
varstep |
boolean value specifying if the method allows for
variable time step (TRUE ) or not (FALSE ).
|
interpolation |
boolean value to switch internal interpolation off. Note that this works only if time steps match exactly. This may not work as expected for all cases because of floating point rounding errors (see R FAQ about ``Why doesn't R think these numbers are equal?''). |
FSAL |
(first same as last) boolean value specifying if the
method allows re-use of the last function evaluation (TRUE )
or not (FALSE or NULL ).
|
A |
coefficient matrix of the method. As link{rk} supports
only explicit methods, this matrix must be lower triangular.
A must be a vector for fixed step methods where only the
subdiagonal values are different from zero.
|
b1 |
weighting coefficients for averaging the function evaluations of method 1. |
b2 |
weighting coefficients for averaging the function evaluations of method 2 (optional, for embedded methods that allow variable time step). |
c |
coefficients for calculating the intermediate time steps. |
d |
coefficients for built-in polynomial interpolation of the
outputs from internal steps (dense output), currently only available
for method rk45dp7 (Dormand-Prince).
|
stage |
number of function evaluations needed (corresponds to number of rows in A). |
Qerr |
global error order of the method, important for automatic time-step adjustment. |
rk
solvers, "rk45dp7" (alias "ode45") is used
by default, because of its relatively high order (4), re-use of
the last intermediate steps (FSAL = first same as last) and
built-in polynomial interpolation (dense output). Solver "rk23bs",
that supports also FSAL, may be useful for slightly stiff systems
if demands on precision are low. Classical "rk4" is traditionally
used in cases where an adequate stepsize is known a-priori or if
external forcing data are provided for fixed time steps only and
frequent interpolation of external data needs to be avoided.
lsoda
, lsode
, lsodes
,
lsodar
, vode
, daspk
) are
superior because of higher efficiency and faster implementation.
In addition to this, some of the Livermore solvers are also
suitable for stiff ODEs, differential algebraic equations (DAEs),
or partial differential equations (PDEs).
Thomas Petzoldt thomas.petzoldt@tu-dresden.de
Bogacki, P. and Shampine L.F. (1989) A 3(2) pair of Runge-Kutta formulas, Appl. Math. Lett. 2, 1–9.
Butcher, J. C. (1987) The numerical analysis of ordinary differential equations, Runge-Kutta and general linear methods, Wiley, Chichester and New York.
Dormand, J. R. and Prince, P. J. (1980) A family of embedded Runge-Kutta formulae, J. Comput. Appl. Math. 6(1), 19–26.
Dormand, J. R. and Prince, P. J. (1981) High order embedded Runge-Kutta formulae, J. Comput. Appl. Math. 7(1), 67–75.
Engeln-Muellges, G. and Reutter, F. (1996) Numerik Algorithmen: Entscheidungshilfe zur Auswahl und Nutzung. VDI Verlag, Duesseldorf.
Fehlberg, E. (1967) Klassische Runge-Kutta-Formeln fuenfter and siebenter Ordnung mit Schrittweiten-Kontrolle, Computing (Arch. Elektron. Rechnen) 4, 93–106.
Kutta, W. (1901) Beitrag zur naeherungsweisen Integration totaler Differentialgleichungen, Z. Math. Phys. 46, 435–453.
Octave-Forge - Extra Packages for GNU Octave, Package OdePkg. http://octave.sourceforge.net/doc/odepkg.html
Runge, C. (1895) Ueber die numerische Aufloesung von Differentialgleichungen, Math. Ann. 46, 167–178.
MATLAB (R) is a registed property of The Mathworks Inc. http://www.mathworks.com/
rkMethod() # returns the names of all available methods rkMethod("rk45dp7") # parameters of the Dormand-Prince 5(4) method rkMethod("ode45") # an alias for the same method func <- function(t, x, parms) { with(as.list(c(parms, x)),{ dP <- a * P - b * K * P dK <- b * P * K - c * K res <- c(dP, dK) list(res) }) } times <- seq(0, 20, length = 21) parms <- c(a = 0.1, b = 0.1, c = 0.1) x <- c(P = 2, K = 1) ode(x, times, func, parms, method = rkMethod("rk4")) ode(x, times, func, parms, method = "ode45") ## disable polynomial interpolation (dense output) ## and fall back to linear approximation ode(x, times, func, parms, method = rkMethod("rk45dp7", d = NULL)) ## define and use a new rk method ode(x, times, func, parms, method = rkMethod(ID = "midpoint", varstep = FALSE, A = c(0, 1/2), b1 = c(0, 1), c = c(0, 1/2), stage = 2, Qerr = 1 ) )