simulate_multilevel_SDE: Simulate two time-discretized process following a stochastic...

In jeremyhengjm/UnbiasedGradients: Unbiased estimators for partially observed diffusions

Simulate two time-discretized process following a stochastic differential equation

Description

Simulate two trajectories following a stochastic differential equation using Euler-Maruyama at two successive discretization levels.

Usage

simulate_multilevel_SDE(model, theta, discretization)

Arguments

model	a list representing a hidden Markov model, e.g. hmm_ornstein_uhlenbeck
theta	a vector of parameters as input to model functions
discretization	lists containing stepsize, nsteps, statelength, obstimes for fine and coarse levels, and coarsetimes of length statelength_fine indexing time steps of coarse level

Value

two new trajectories stored as matrices of size xdimension x statelength_coarse/fine.

jeremyhengjm/UnbiasedGradients documentation built on Nov. 19, 2023, 11:24 p.m.