simulate_SDE: Simulate time-discretized process following a stochastic...
In jeremyhengjm/UnbiasedScore: Unbiased estimators for partially observed diffusions
simulate_SDE R Documentation
Simulate time-discretized process following a stochastic differential equation
Description
Simulate a trajectory following a stochastic differential equation using Euler-Maruyama discretization.
Usage
simulate_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
list containing stepsize, nsteps and statelength
Value
a matrix containing a new trajectory of size xdimension x statelength.
jeremyhengjm/UnbiasedScore documentation built on Nov. 17, 2023, 1:48 a.m.
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| simulate_SDE | R Documentation |
Simulate time-discretized process following a stochastic differential equation
Description
Simulate a trajectory following a stochastic differential equation using Euler-Maruyama discretization.
Usage
simulate_SDE(model, theta, discretization)
Arguments
model |
a list representing a hidden Markov model, e.g. |
theta |
a vector of parameters as input to model functions |
discretization |
list containing stepsize, nsteps and statelength |
Value
a matrix containing a new trajectory of size xdimension x statelength.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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