Exctract field and parameter values and distributions for an inla.spde SPDE effect from an inla result object.

inla.spde.result(...)

# S3 method for class 'inla.spde1'
inla.spde.result(inla, name, spde, do.transform = TRUE, ...)
# S3 method for class 'inla.spde2'
inla.spde.result(inla, name, spde, do.transform = TRUE, ...)

## Direct function call for class 'inla.spde1':
inla.spde1.result(inla, name, spde, do.transform = TRUE, ...)
## Direct function call for class 'inla.spde2':
inla.spde2.result(inla, name, spde, do.transform = TRUE, ...)

Arguments

inla

An inla object obtained from a call to inla

name

A character string with the name of the SPDE effect in the inla formula.

spde

The inla.spde object used for the effect in the inla formula. (Note: this could have been stored in the inla output, but isn't.) Usually the result of a call to inla.spde2.matern.

do.transform

If TRUE, also calculate marginals transformed to user-scale. Setting to FALSE is useful for large non-stationary models, as transforming many marginal densities is time-consuming.

...

Further arguments passed to and from other methods.

Value

For inla.spde2 models, a list, where the nominal range and variance are defined as the values that would have been obtained with a stationary model and no boundary effects:

marginals.kappa

Marginal densities for kappa

marginals.log.kappa

Marginal densities for log(kappa)

marginals.log.range.nominal

Marginal densities for log(range)

marginals.log.tau

Marginal densities for log(tau)

marginals.log.variance.nominal

Marginal densities for log(variance)

marginals.range.nominal

Marginal densities for range

marginals.tau

Marginal densities for tau

marginals.theta

Marginal densities for the theta parameters

marginals.values

Marginal densities for the field values

marginals.variance.nominal

Marginal densities for variance

summary.hyperpar

The SPDE related part of the inla hyperpar output summary

summary.log.kappa

Summary statistics for log(kappa)

summary.log.range.nominal

Summary statistics for log(range)

summary.log.tau

Summary statistics for log(tau)

summary.log.variance.nominal

Summary statistics for log(kappa)

summary.theta

Summary statistics for the theta parameters

summary.values

Summary statistics for the field values

Author

Finn Lindgren finn.lindgren@gmail.com

Examples

loc = matrix(runif(100*2),100,2)
mesh = inla.mesh.create.helper(points.domain=loc, max.edge=c(0.1,0.5))
#> Warning: error in running command
#> Error in fmesher.read(prefix, "manifold"): File '/tmp/Rtmp4ztB6d/fmesher53bd142cc5fa.manifold' does not exist.
spde = inla.spde2.matern(mesh)
#> Error: object 'mesh' not found
index = inla.spde.make.index("spatial", mesh$n, n.repl=2)
#> Error: object 'mesh' not found
spatial.A = inla.spde.make.A(mesh, loc,
                             index=rep(1:nrow(loc), 2),
                             repl=rep(1:2, each=nrow(loc)))
#> Error: object 'mesh' not found
## Toy example with no spatial correlation (range=zero)
y = 10+rnorm(100*2)
stack = inla.stack(data=list(y=y),
                   A=list(spatial.A),
                   effects=list(c(index, list(intercept=1))),
                   tag="tag")
#> Error: object 'spatial.A' not found
data = inla.stack.data(stack, spde=spde)
#> Error in inla.require.inherits(stack, "inla.data.stack", "'stack'"): 'stack' must inherit from class "inla.data.stack".
formula = y ~ -1 + intercept + f(spatial, model=spde,
                                 replicate=spatial.repl)
result = inla(formula, family="gaussian", data=data, 
              control.predictor=list(A=inla.stack.A(stack)))
#> Error in inla(formula, family = "gaussian", data = data, control.predictor = list(A = inla.stack.A(stack))): 
#> 	Argument `data' must be a data.frame or a list.
spde.result = inla.spde.result(result, "spatial", spde)
#> Error: object 'result' not found
plot(spde.result$marginals.range.nominal[[1]], type="l")
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'spde.result' not found