evmc: Simulate Markov Chains With Extreme Value Dependence...

In evd: Functions for Extreme Value Distributions

Simulate Markov Chains With Extreme Value Dependence Structures

Description

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.

Usage

evmc(n, dep, asy = c(1,1), alpha, beta, model = c("log", "alog",
    "hr", "neglog", "aneglog", "bilog", "negbilog", "ct", "amix"),
    margins = c("uniform","rweibull","frechet","gumbel"))

Arguments

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 reverse Weibull, standard Gumbel and standard Frechet distributions respectively.

Value

A numeric vector of length n.

See Also

marma, rbvevd

Examples

evmc(100, alpha = 0.1, beta = 0.1, model = "bilog")
evmc(100, dep = 10, model = "hr", margins = "gum")

evd documentation built on Sept. 21, 2024, 9:06 a.m.