SpatialExtremes (version 2.0-7)

profile2d: Method for profiling (in 2d) fitted max-stable objects

Description

Computes profile surfaces for fitted max-stable models.

Usage

# S3 method for 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!

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)
# }