View source: R/simulation_functions.R
rmstable | R Documentation |
Simulates exact samples of a multivariate max-stable distribution.
rmstable(n, model = c("HR", "logistic", "neglogistic", "dirichlet")[1], d, par)
n |
Number of simulations. |
model |
The parametric model type; one of:
|
d |
Dimension of the multivariate Pareto distribution. |
par |
Respective parameter for the given
|
The simulation follows the extremal function algorithm in \insertCitedom2016;textualgraphicalExtremes. For details on the parameters of the Huesler-Reiss, logistic and negative logistic distributions see \insertCitedom2016;textualgraphicalExtremes, and for the Dirichlet distribution see \insertCitecoles1991modelling;textualgraphicalExtremes.
Numeric \nxd matrix of simulations of the multivariate max-stable distribution.
Other sampling functions:
rmpareto()
,
rmpareto_tree()
,
rmstable_tree()
## A 4-dimensional HR distribution
n <- 10
d <- 4
G <- cbind(
c(0, 1.5, 1.5, 2),
c(1.5, 0, 2, 1.5),
c(1.5, 2, 0, 1.5),
c(2, 1.5, 1.5, 0)
)
rmstable(n, "HR", d = d, par = G)
## A 3-dimensional logistic distribution
n <- 10
d <- 3
theta <- .6
rmstable(n, "logistic", d, par = theta)
## A 5-dimensional negative logistic distribution
n <- 10
d <- 5
theta <- 1.5
rmstable(n, "neglogistic", d, par = theta)
## A 4-dimensional Dirichlet distribution
n <- 10
d <- 4
alpha <- c(.8, 1, .5, 2)
rmstable(n, "dirichlet", d, par = alpha)
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