simSPDE: Simulate from the SPDE spatial model

In bryandmartin/SUMMER: Small-Area-Estimation Unit/Area Models and Methods for Estimation in R

Simulate from the SPDE spatial model

Description

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

Author(s)

John Paige

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.

Examples

## Not run: 
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)

## End(Not run)

bryandmartin/SUMMER documentation built on April 9, 2024, 10:27 a.m.