inst/examples/generate.bru.R

In inlabru-org/inlabru: Bayesian Latent Gaussian Modelling using INLA and Extensions

\donttest{
if (bru_safe_inla(multicore = FALSE) &&
    require("sn", quietly = TRUE)) {

  # Generate data for a simple linear model

  input.df <- data.frame(x = cos(1:10))
  input.df <- within(input.df, y <- 5 + 2 * cos(1:10) + rnorm(10, mean = 0, sd = 0.1))

  # Fit the model

  fit <- bru(y ~ xeff(main = x, model = "linear"),
    family = "gaussian", data = input.df
  )
  summary(fit)

  # Generate samples for some predefined x

  df <- data.frame(x = seq(-4, 4, by = 0.1))
  smp <- generate(fit, df, ~ xeff + Intercept, n.samples = 10)

  # Plot the resulting realizations

  plot(df$x, smp[, 1], type = "l")
  for (k in 2:ncol(smp)) points(df$x, smp[, k], type = "l")

  # We can also draw samples form the joint posterior

  df <- data.frame(x = 1)
  smp <- generate(fit, df, ~ data.frame(xeff, Intercept), n.samples = 10)
  smp[[1]]

  # ... and plot them
  if (require(ggplot2, quietly = TRUE)) {
    plot(do.call(rbind, smp))
  }
}
}