simulate,mixedDiffusion-method {BaPreStoPro} | R Documentation |
Simulation of the stochastic process model dY_t = b(φ_j,t,Y_t)dt + γ \widetilde{s}(t,Y_t)dW_t, φ_j~N(μ, Ω).
## S4 method for signature 'mixedDiffusion' simulate(object, nsim = 1, seed = NULL, t, mw = 1, plot.series = TRUE)
object |
class object of parameters: "mixedDiffusion" |
nsim |
number of data sets to simulate. Default is 1. |
seed |
optional: seed number for random number generator |
t |
vector of time points |
mw |
mesh width for finer Euler approximation to simulate time-continuity |
plot.series |
logical(1), if TRUE, simulated series are depicted grafically |
mu <- 2; Omega <- 0.4; phi <- matrix(rnorm(21, mu, sqrt(Omega))) model <- set.to.class("mixedDiffusion", y0.fun = function(phi, t) 0.5, parameter = list(phi = phi, mu = mu, Omega = Omega, gamma2 = 0.1), b.fun = function(phi, t, x) phi*x, sT.fun = function(t, x) x) t <- seq(0, 1, by = 0.01) data <- simulate(model, t = t, plot.series = TRUE)