spde.posterior: Posteriors of SPDE hyper parameters and Matern correlation or...

In inlabru: Bayesian Latent Gaussian Modelling using INLA and Extensions

Posteriors of SPDE hyper parameters and Matern correlation or covariance function.

Description

Calculate posterior distribution of the range, log(range), variance, or log(variance) parameter of a model's SPDE component. Can also plot Matern correlation or covariance function. inla.spde.result.

Usage

spde.posterior(result, name, what = "range", quantile = 0.95)

Arguments

result	An object inheriting from inla.
name	Character stating the name of the SPDE effect, see names(result$summary.random).
what	One of "range", "log.range", "variance", "log.variance", "matern.correlation" or "matern.covariance".
quantile	The target credible probability. Default 0.95.

Value

A prediction object.

Author(s)

Finn Lindgren [e-mail]

Examples

if (bru_safe_inla() && require(ggplot2, quietly = TRUE)) {

  # Load 1D Poisson process data

  data(Poisson2_1D, package = "inlabru")


  # Take a look at the point (and frequency) data

  ggplot(pts2) +
    geom_histogram(aes(x = x), binwidth = 55 / 20, boundary = 0, fill = NA, color = "black") +
    geom_point(aes(x), y = 0, pch = "|", cex = 4) +
    coord_fixed(ratio = 1)

  # Fit an LGCP model with  and SPDE component

  x <- seq(0, 55, length.out = 20)
  mesh1D <- fm_mesh_1d(x, boundary = "free")
  mdl <- x ~ spde1D(x, model = INLA::inla.spde2.matern(mesh1D, constr = TRUE)) + Intercept(1)
  fit <- lgcp(mdl, data = pts2, domain = list(x = mesh1D))

  # Calculate and plot the posterior range

  range <- spde.posterior(fit, "spde1D", "range")
  plot(range)

  # Calculate and plot the posterior log range

  lrange <- spde.posterior(fit, "spde1D", "log.range")
  plot(lrange)

  # Calculate and plot the posterior variance

  variance <- spde.posterior(fit, "spde1D", "variance")
  plot(variance)

  # Calculate and plot the posterior log variance

  lvariance <- spde.posterior(fit, "spde1D", "log.variance")
  plot(lvariance)

  # Calculate and plot the posterior Matern correlation

  matcor <- spde.posterior(fit, "spde1D", "matern.correlation")
  plot(matcor)

  # Calculate and plot the posterior Matern covariance

  matcov <- spde.posterior(fit, "spde1D", "matern.covariance")
  plot(matcov)
}

inlabru documentation built on Aug. 9, 2025, 1:08 a.m.