rmaxstab {SpatialExtremes} | R Documentation |
This functions generates realisation from a max-stable random field.
rmaxstab(n, coord, cov.mod = "gauss", grid = FALSE, ...)
n |
Integer. The number of observations. |
coord |
A vector or matrix that gives the coordinates of each location. Each row corresponds to one location - if any. |
cov.mod |
A character string that gives the max-stable model. This must be one of "gauss" for the Smith model or "whitmat", "cauchy", "powexp" and "bessel" for the Schlather model with the given correlation family. |
grid |
Logical. Does the coordinates represent grid points? |
... |
The parameters of the max-stable model. See details. |
Users must supply the parameters for the max-stable model. For the
Schlather model, users should supply the "sill", "range" and "smooth"
parameter values. For the Smith model, if coord
is univariate
you must specify var
, otherwise users should supply the
covariance parameters i.e. parameters with names such as cov11
,
cov12
, ...
A matrix containing observations from the required max-stable
model. Each column represents one stations. If grid = TRUE
, the
function returns an array of dimension nrow(coord) x nrow(coord) x n.
Mathieu Ribatet
Schlather, M. (2002) Models for Stationary Max-Stable Random Fields. Extremes 5:1, 33–44.
Smith, R. L. (1990) Max-stable processes and spatial extremes. Unpublished manuscript.
\fitmaxstab
## 1. Smith's model set.seed(8) x <- seq(0, 10, length = 200) coord <- cbind(x, x) data <- rmaxstab(1, coord, cov11 = 9/8, cov12 = 0, cov22 = 9/8, grid = TRUE) ##We change the margins for visibility filled.contour(x, x, sqrt(data[,,1])) ## 2. Schlather's model coord <- matrix(runif(100, 0, 15), ncol = 2) data <- rmaxstab(100, coord, cov.mod = "whitmat", sill = 1, range = 10, smooth = 1)