R: Method for profiling (in 2d) fitted max-stable objects

profile2d {SpatialExtremes} | R Documentation

## Method for profiling (in 2d) fitted max-stable objects

### Description

Computes profile surfaces for fitted max-stable models.

### Usage

    ## S3 method for class 'maxstab'
    profile2d(fitted, params, ranges, n = 10, plot = TRUE,
    ...)

### Arguments

`fitted` | An object of class “maxstab”. Most often, it will be the output of the function `fitmaxstab`.
`params` | A character vector giving the two model parameters that are to be profiled.
`ranges` | A matrix corresponding to the ranges for the profiled model parameters that must be explored. Each row corresponds to one model parameter range.
`n` | Integer. The number of profiled model parameter that must be considered.
`plot` | Logical. If `TRUE` (default), the profile surface is plotted.
`...` | Extra options that must be passed to the `plot` function.

### Value

A list with two arguments: `coord` and `llik`. `coord` is a matrix representing the grid where the profiled model parameters are fixed. `llik` the corresponding pairwise log-likelihood.

### Warnings

This function can be really time consuming!

### Author(s)

Mathieu Ribatet

### Examples

    ## Not run:
    ##Define the coordinates of each location
    n.site <- 30
    locations <- matrix(rnorm(2*n.site, sd = sqrt(.2)), ncol = 2)
    colnames(locations) <- c("lon", "lat")

    ##Simulate a max-stable process - with unit Frechet margins
    data <- rmaxstab(30, locations, cov.mod = "whitmat", nugget = 0, range = 30,
    smooth = 0.5)

    ##Now define the spatial model for the GEV parameters
    param.loc <- -10 + 2 * locations[,2]
    param.scale <- 5 + 2 * locations[,1] + locations[,2]^2
    param.shape <- rep(0.2, n.site)

    ##Transform the unit Frechet margins to GEV
    for (i in 1:n.site)
      data[,i] <- frech2gev(data[,i], param.loc[i], param.scale[i],
    param.shape[i])

    ##Define a model for the GEV margins to be fitted
    ##shape ~ 1 stands for the GEV shape parameter is constant
    ##over the region
    loc.form <- loc ~ lat
    scale.form <- scale ~ lon + (lat^2)
    shape.form <- shape ~ 1

    ##Fit a max-stable process
    ##  1- using the Schlather representation
    fitted <- fitmaxstab(data, locations, "whitmat", loc.form, scale.form,
                         shape.form)

    ##Plot the profile pairwise log-likelihood for the smooth parameter
    ranges <- rbind(c(9,11), c(.3, .8))
    profile2d(fitted, c("range", "smooth"), ranges = ranges)

    ## End(Not run)

[Package SpatialExtremes version 2.0-5 Index]