simulate_sde: Simulate Langevin Equations

In citiususc/voila: Variational Inference for Langevin Equations

Description

A simple wrapper for yuima's SDE simulation methods

Usage

simulate_sde(driftExpression, diffExpression, samplingPeriod, tsLength,
  stateVariable = "x", xinit, trueParameter = list())

Arguments

driftExpression, diffExpression	A string/expression specifying the drift and diffusion terms
samplingPeriod	The sampling period of the resulting time series
tsLength	The length of the resulting time series
stateVariable	Vector of names of the variables used in the drift and diffusion equations.
xinit	Initial value for the resulting time series
trueParameter	A list containing the true parameters of the drift and diffusion expressions (in the case that there are some unknown values).

Value

A matrix containing the simulated trajectory.

See Also

simulate

Examples

simTs = simulate_sde("-x", "sqrt(2)", 0.001, 1000)
plot.ts(simTs, xlab = "Time t", ylab = "x(t)",
        main = "Ornstein-Uhlenbeck process")

citiususc/voila documentation built on May 13, 2019, 7:30 p.m.