**sde_test**,
a MATLAB code which
calls sde(), which
illustrates the properties of stochastic differential equations (SDE) and some
algorithms for handling them.

The computer code and data files made available on this web page are distributed under the GNU LGPL license.

sde, a MATLAB code which illustrates properties of stochastic ordinary differential equations (SODE's), and common algorithms for their analysis, including the Euler method, the Euler-Maruyama method, and the Milstein method, by Desmond Higham;

- sde_test.m, calls all the tests.
- sde_test.sh, runs all the tests.
- sde_test.txt, the output file.

- stochastic_integral_ito_test.m, tests stochastic_integral_ito.
- stochastic_integral_strat_test.m, tests stochastic_integral_strat.

A number of graphics images are created by the example programs:

- bpath.png, an image of the computed path for BPATH.
- bpath_vectorized.png, an image of the computed path for BPATH_VECTORIZED.
- bpath_average.png, an image of the averaged paths for BPATH_AVERAGE.
- chain.png, an image comparing solutions done with and without the chain rule.
- em.png, an image of a true solution versus the Euler-Maruyama estimate.
- emstrong.png, an image of the strong convergence of the Euler-Maruyama error with stepsize.
- emweak0.png, an image of the weak convergence of the standard Euler-Maruyama method.
- emweak1.png, an image of the weak convergence of the weak Euler-Maruyama method.
- milstrong.png, an image of the strong convergence of the Milstein method.
- stab_asymptotic.png, an image of an asymptotic stability check.
- stab_meansquare.png, an image of a meansquare stability check.