simulate-Merton-method: Simulation of jump diffusion process
In SimoneHermann/BaPreStoPro: Bayesian Prediction of Stochastic Processes

Simulation of jump diffusion process Y_t = y_0 \exp( φ t - γ^2/2 t+γ W_t + \log(1+θ) N_t).

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## S4 method for signature 'Merton'
simulate(object, nsim = 1, seed = NULL, t, y0,
  start = c(0, 0), plot.series = TRUE)

`object`	class object of parameters: "Merton"
`nsim`	number of trajectories to simulate. Default is 1.
`seed`	optional: seed number for random number generator
`t`	vector of time points
`y0`	starting point of process
`start`	vector: start[1] starting point time, start[2] starting point for Poisson process
`plot.series`	logical(1), if TRUE, simulated series are depicted grafically

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model <- set.to.class("Merton", parameter = list(thetaT = 0.1, phi = 0.05, gamma2 = 0.1, xi = 10))
t <- seq(0, 1, by = 0.01)
data <- simulate(model, t = t, y0 = 0.5)