fitcovmat | R Documentation |
Estimates the covariance matrix for the Smith's model using non-parametric estimates of the pairwise extremal coefficients.
fitcovmat(data, coord, marge = "emp", iso = FALSE, control = list(), ..., start, weighted = TRUE)
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. |
marge |
Character string specifying how margins are transformed
to unit Frechet. Must be one of "emp", "frech" or "mle" - see
function |
iso |
Logical. If |
control |
The control arguments to be passed to the
|
... |
Optional arguments to be passed to the |
start |
A named list giving the initial values for the
parameters over which the weighted sum of square is to be
minimized. If |
weighted |
Logical. Should weighted least squares be used? |
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 Smith's model and
s_{i,j} are the standard errors related to the
estimates θ_{i,j}^+.
An object of class maxstab.
Mathieu Ribatet
Smith, R. L. (1990) Max-stable processes and spatial extremes. Unpublished manuscript.
fitcovariance
, fitmaxstab
,
fitextcoeff
n.site <- 50 n.obs <- 100 locations <- matrix(runif(2*n.site, 0, 40), ncol = 2) colnames(locations) <- c("lon", "lat") ## Simulate a max-stable process - with unit Frechet margins data <- rmaxstab(50, locations, cov.mod = "gauss", cov11 = 200, cov12 = 0, cov22 = 200) fitcovmat(data, locations) ##Force an isotropic model fitcovmat(data, locations, iso = TRUE)
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