Description Usage Arguments Examples
Simulation of regression model y_{ij} = f(φ_j, t_{ij}) + ε_{ij}, φ_j\sim N(μ, Ω), ε_{ij}\sim N(0,γ^2\widetilde{s}(t_{ij})).
1 2 3 |
object |
class object of parameters: "mixedRegression" |
nsim |
number of data sets 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 |
1 2 3 4 5 6 | mu <- 2; Omega <- 0.4; phi <- matrix(rnorm(21, mu, sqrt(Omega)))
model <- set.to.class("mixedRegression",
parameter = list(phi = phi, mu = mu, Omega = Omega, gamma2 = 0.1),
fun = function(phi, t) phi*t, sT.fun = function(t) t)
t <- seq(0, 1, by = 0.01)
data <- simulate(model, t = t, plot.series = TRUE)
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