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(...)

    inla.spde1.result(inla, name, spde, do.transform = TRUE, ...)

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

    inla.spde2.result(inla, name, spde, do.transform = TRUE, ...)

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

### Arguments

`...` | Further arguments passed to and from other methods.
`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.

### 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 <- fmesher::fm_mesh_2d_inla(loc.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 25.06.07 Index]