fitcovariance: Estimates the covariance function for the Schlather's model

In SpatialExtremes: Modelling Spatial Extremes

Estimates the covariance function for the Schlather's model

Description

Estimates the covariance function for the Schlather's model using non-parametric estimates of the pairwise extremal coefficients.

Usage

fitcovariance(data, coord, cov.mod, marge = "emp", control = list(),
..., start, weighted = TRUE)

Arguments

data	A matrix representing the data. Each column corresponds to one location.
coord	A matrix that gives the coordinates of each location. Each row corresponds to one location.
cov.mod	A character string corresponding the the covariance model in the Schlather's model. Must be one of "whitmat", "cauchy", "powexp", "bessel" or "caugen" for the Whittle-Matern, the Cauchy, the Powered Exponential, the Bessel and the Generalized Cauchy correlation families.
marge	Character string specifying how margins are transformed to unit Frechet. Must be one of "emp", "frech" or "mle" - see function fitextcoeff.
control	The control arguments to be passed to the optim function.
...	Optional arguments to be passed to the optim function.
start	A named list giving the initial values for the parameters over which the weighted sum of square is to be minimized. If start is omitted the routine attempts to find good starting values.
weighted	Logical. Should weighted least squares be used?

Details

The fitting procedure is based on weighted least squares. More precisely, the fitting criteria is to minimize:

∑_{i,j} [(θ_{i,j}^+ - θ_{i,j}^*) / s_{i,j}]^2

where θ_{i,j}^+ is a non parametric estimate of the extremal coefficient related to location i and j, θ_{i,j}^* is the fitted extremal coefficient derived from the Schlather's model and s_{i,j} are the standard errors related to the estimates θ_{i,j}^+.

Value

An object of class maxstab.

Author(s)

Mathieu Ribatet

References

Smith, R. L. (1990) Max-stable processes and spatial extremes. Unpublished manuscript.

See Also

fitcovmat, fitmaxstab, fitextcoeff

Examples

n.site <- 50
locations <- matrix(runif(2*n.site, 0, 10), ncol = 2)
colnames(locations) <- c("lon", "lat")

##Simulating a max-stable process using RandomFields
##This is the Schlather's approach
data <- rmaxstab(50, locations, cov.mod = "whitmat", nugget = 0, range =
30, smooth = 1)

fitcovariance(data, locations, "whitmat")

SpatialExtremes documentation built on April 19, 2022, 5:06 p.m.