evmc {evd} | R Documentation |
Simulation of first order Markov chains, such that each pair of consecutive values has the dependence structure of one of nine parametric bivariate extreme value distributions.
evmc(n, dep, asy = c(1,1), alpha, beta, model = "log", margins = "uniform")
n |
Number of observations. |
dep |
Dependence parameter for the logistic, asymmetric logistic, Husler-Reiss, negative logistic and asymmetric negative logistic models. |
asy |
A vector of length two, containing the two asymmetry parameters for the asymmetric logistic and asymmetric negative logistic models. |
alpha, beta |
Alpha and beta parameters for the bilogistic, negative bilogistic, Coles-Tawn and asymmetric mixed models. |
model |
The specified model; a character string. Must be
either "log" (the default), "alog" , "hr" ,
"neglog" , "aneglog" , "bilog" ,
"negbilog" , "ct" or "amix" (or any unique
partial match), for the logistic, asymmetric logistic,
Husler-Reiss, negative logistic, asymmetric negative logistic,
bilogistic, negative bilogistic, Coles-Tawn and asymmetric mixed
models respectively. The definition of each model is given in
rbvevd . If parameter arguments are given that do
not correspond to the specified model those arguments are
ignored, with a warning. |
margins |
The marginal distribution of each value; a
character string. Must be either "uniform" (the
default), "rweibull" , "frechet" or
"gumbel" (or any unique partial match), for the uniform,
standard reversed Weibull, standard Gumbel and standard Frechet
distributions respectively. |
A numeric vector of length n
.
evmc(100, alpha = 0.1, beta = 0.1, model = "bilog") evmc(100, dep = 10, model = "hr", margins = "gum")