Simulate from the SPDE spatial model

Generates nCoords x nsim matrix of simulated values of the SPDE spatial process

Usage

simSPDE(
  coords,
  nsim = 1,
  mesh,
  effRange = (max(coords[, 1]) - min(coords[, 1]))/3,
  margVar = 1,
  inla.seed = 0L
)

Arguments

coords: 2 column matrix of spatial coordinates at which to simulate the spatial process
nsim: number of draws from the SPDE model
mesh: SPDE mesh
effRange: effective spatial range
margVar: marginal variance of the spatial process
inla.seed: seed input to inla.qsample. 0L sets seed intelligently, > 0 sets a specific seed, < 0 keeps existing RNG

References

Lindgren, F., Rue, H., Lindström, J., 2011. An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic differential equation approach (with discussion). Journal of the Royal Statistical Society, Series B 73, 423–498.

Author

John Paige

Examples

if (FALSE) { # \dontrun{
set.seed(123)
require(INLA)
coords = matrix(runif(10*2), ncol=2)
mesh = inla.mesh.2d(loc.domain=cbind(c(0, 0, 1, 1), c(0, 1, 0, 1)), 
  n=3000, max.n=5000, max.edge=c(.01, .05), offset=-.1)
simVals = simSPDE(coords, nsim=1, mesh, effRange=.2, inla.seed=1L)
} # }