BaPreStoPro (version 0.1)

simulate,jumpRegression-method: Simulation of regression model dependent on Poisson process

Description

Simulation of of the regression model $y_i = f(t_i, N_{t_i}, \theta) + \epsilon_i$ with $N_t\sim Pois(\Lambda(t, \xi)), \epsilon_i\sim N(0,\gamma^2\widetilde{s}(t))$.

Usage

"simulate"(object, nsim = 1, seed = NULL, t, plot.series = TRUE)

Arguments

object

class object of parameters: "jumpRegression"

nsim

number of trajectories to simulate. Default is 1.

seed

optional: seed number for random number generator

t

vector of time points

plot.series

logical(1), if TRUE, simulated series are depicted grafically

Examples

model <- set.to.class("jumpRegression", fun = function(t, N, theta) theta[1]*t + theta[2]*N,
   parameter = list(theta = c(1,2), gamma2 = 0.1, xi = 10))
t <- seq(0, 1, by = 0.01)
data <- simulate(model, t = t)