Simulates the model equations of gs_spec() with innovations drawn from
the model's distribution. The recursion starts at the unconditional
location and scale level and the first burnin values are discarded.
Usage
gs_sim(model, n = 1000, burnin = 1000, seed = NULL)
Arguments
- model
A gs_model object.
- n
Length of the returned series.
- burnin
Number of initial values discarded.
- seed
Optional seed passed to set.seed().
Value
A data frame with columns y (series), sigma (conditional scale)
and z (innovations).
Examples
spec <- gs_spec(arma = c(1, 0), garch = c(1, 1), dist = gs_stable())
model <- gs_model(spec, mu = 0, ar = 0.1, omega = 0.05, alpha = 0.1, beta = 0.8,
dist_par = c(stable_alpha = 1.8, stable_beta = 0))
x <- gs_sim(model, n = 500, seed = 1)
plot(x$y, type = "l")
