inla.spde.result {INLA} | R Documentation

## SPDE result extraction from INLA estimation results

### Description

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

### Usage

    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(s)

Finn Lindgren finn.lindgren@gmail.com

### See Also

`inla.spde.models`, `inla.spde2.matern`

### Examples

    loc = matrix(runif(100*2),100,2)
    mesh = inla.mesh.create.helper(points.domain=loc, max.edge=c(0.1,0.5))
    spde = inla.spde2.matern(mesh)
    index = inla.spde.make.index("spatial", mesh$n, n.repl=2)
    spatial.A = inla.spde.make.A(mesh, loc,
                                 index=rep(1:nrow(loc), 2),
                                 repl=rep(1:2, each=nrow(loc)))
    ## Toy example with no spatial correlation (range=zero)
    y = 10+rnorm(100*2)
    stack = inla.stack(data=list(y=y),
                       A=list(spatial.A),
                       effects=list(c(index, list(intercept=1))),
                       tag="tag")
    data = inla.stack.data(stack, spde=spde)
    formula = y ~ -1 + intercept + f(spatial, model=spde,
                                     replicate=spatial.repl)
    result = inla(formula, family="gaussian", data=data,
                  control.predictor=list(A=inla.stack.A(stack)))
    spde.result = inla.spde.result(result, "spatial", spde)
    plot(spde.result$marginals.range.nominal[[1]], type="l")

[Package INLA version 18.07.12 Index]