spde.make.A: Observation/prediction matrices for rSPDE models with integer...

In rSPDE: Rational Approximations of Fractional Stochastic Partial Differential Equations

Observation/prediction matrices for rSPDE models with integer smoothness.

Description

Constructs observation/prediction weight matrices for rSPDE models with integer smoothness based on inla.mesh or inla.mesh.1d objects.

Usage

spde.make.A(
  mesh = NULL,
  loc = NULL,
  A = NULL,
  index = NULL,
  group = NULL,
  repl = 1L,
  n.group = NULL,
  n.repl = NULL
)

Arguments

mesh	An inla.mesh, an inla.mesh.1d object or a metric_graph object.
loc	Locations, needed if an INLA mesh is provided
A	The A matrix from the standard SPDE approach, such as the matrix returned by inla.spde.make.A. Should only be provided if mesh is not provided.
index	For each observation/prediction value, an index into loc. Default is seq_len(nrow(A.loc)).
group	For each observation/prediction value, an index into the group model.
repl	For each observation/prediction value, the replicate index.
n.group	The size of the group model.
n.repl	The total number of replicates.

Value

The A matrix for rSPDE models.

Examples

 #tryCatch version
tryCatch({
if (requireNamespace("fmesher", quietly = TRUE)){
library(fmesher)

set.seed(123)
loc <- matrix(runif(100 * 2) * 100, 100, 2)
mesh <- fm_mesh_2d(
  loc = loc,
  cutoff = 50,
  max.edge = c(50, 500)
)
A <- spde.make.A(mesh, loc = loc)
}
#stable.tryCatch
}, error = function(e){print("Could not run the example")})

rSPDE documentation built on Nov. 6, 2023, 1:06 a.m.