R: Bulirsch-Stoer Algorithm

bulirsch-stoer {pracma} | R Documentation

## Bulirsch-Stoer Algorithm

### Description

Bulirsch-Stoer algorithm for solving Ordinary Differential Equations (ODEs) very accurately.

### Usage

    bulirsch_stoer(f, t, y0, ..., tol = 1e-07)

    midpoint(f, t0, tfinal, y0, tol = 1e-07, kmax = 25)

### Arguments

`f` | function describing the differential equation y' = f(t, y).
`t` | vector of `x`-values where the values of the ODE function will be computed; needs to be increasingly sorted.
`y0` | starting values as column vector.
`...` | additional parameters to be passed to the function.
`tol` | relative tolerance in the Ricardson extrapolation.
`t0, tfinal` | start and end point of the interval.
`kmax` | maximal number of steps in the Richardson extrapolation.

### Details

The Bulirsch-Stoer algorithm is a well-known method to obtain high-accuracy solutions to ordinary differential equations with reasonable computational efforts. It exploits the midpoint method to get good accuracy in each step.

The (modified) midpoint method computes the values of the dependent variable `y(t)` from `t0` to `tfinal` by a sequence of substeps, applying Richardson extrapolation in each step.

Bulirsch-Stoer and midpoint shall not be used with non-smooth functions or singularities inside the interval. The best way to get intermediate points `t = (t[1], ..., t[n])` may be to call `ode23` or `ode23s` first and use the `x`-values returned to start `bulirsch_stoer` on.

### Value

bulirsch_stoer returns a list with `x` the grid points input, and `y` a vector of function values at the se points.

### Note

Will be extended to become a full-blown Bulirsch-Stoer implementation.

### Author(s)

Copyright (c) 2014 Hans W Borchers

### References

J. Stoer and R. Bulirsch (2002). Introduction to Numerical Analysis. Third Edition, Texts in Applied Mathematics 12, Springer Science + Business, LCC, New York.

### See Also

`ode23`, `ode23s`

### Examples

    ## Example: y'' = -y
    f1 <- function(t, y) as.matrix(c(y[2], -y[1]))
    y0 <- as.matrix(c(0.0, 1.0))
    tt <- linspace(0, pi, 13)
    yy <- bulirsch_stoer(f1, tt, c(0.0, 1.0))   # 13 equally-spaced grid points
    yy[nrow(yy), 1]                             # 1.1e-11

    ## Not run:
    S  <- ode23(f1, 0, pi, c(0.0, 1.0))
    yy <- bulirsch_stoer(f1, S$t, c(0.0, 1.0))  # S$x 13 irregular grid points
    yy[nrow(yy), 1]                             #  2.5e-11
    S$y[nrow(S$y), 1]                           # -7.1e-04

    ## Example: y' = -200 x y^2                 # y(x) = 1 / (1 + 100 x^2)
    f2 <- function(t, y) -200 * t * y^2
    y0 < 1
    tic(); S <- ode23(f2, 0, 1, y0); toc()            # 0.002 sec
    tic(); yy <- bulirsch_stoer(f2, S$t, y0); toc()   # 0.013 sec
    ## End(Not run)

[Package pracma version 2.0.4 Index]