sde_milstein: Milstein method for solving autonomous SDEs

In shill1729/sdes: Stochastic differential equation solver

Description

A straight forward implementation of the Milstein method for solving SDEs via stochastic integration. The Milstein scheme has both weak and strong order of convergence on the order of the time-step, which is superior to the Euler-Maruyama scheme's square root of time order for strong convergence.

Usage

sde_milstein(x0, tt, drift, diffusion, diff1 = NULL, n = 1000)

Arguments

x0	the initial point of the process
tt	the time horizon to solve over
drift	the infinitesimal drift coefficient, a single-variable function of space
diffusion	the infinitesimal diffusion coefficient, a single-variable function of space
diff1	the derivative of the diffusion coefficient function, can be NULL for numerical approximations.
n	number of sub-intervals to use in time-interval partition

Details

The derivative of the diffusivity coefficient function may be NULL and approximated numerically.

Value

data.frame

shill1729/sdes documentation built on Aug. 30, 2021, 6:36 p.m.