POT (version 1.1-7)

simmc: 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

simmc(n, alpha, model = "log", asCoef, asCoef1, asCoef2, margins =
"uniform")

Arguments

n

Number of observations.

alpha

Dependence parameter for the logistic, asymmetric logistic, negative logistic, asymmetric negative logistic, mixed and asymmetric mixed models.

asCoef,asCoef1,asCoef2

The asymmetric coefficients for the asymmetric logistic, asymmetric negative logistic and asymmetric mixed models.

model

The specified model; a character string. Must be either "log" (the default), "alog", "nlog", "anlog", "mix" or "amix", for the logistic, asymmetric logistic, negative logistic, asymmetric negative logistic, mixed and asymmetric mixed models respectively.

margins

The marginal distribution of each value; a character string. Must be either "uniform" (the default), "rweibull", "frechet" or "gumbel", for the uniform, standard reversed Weibull, standard Gumbel and standard Frechet distributions respectively.

Value

A numeric vector of length n.

Examples

# NOT RUN {
simmc(100, alpha = 0.1, model = "log")
simmc(100, alpha = 1.2, model = "nlog", margins = "gum")
# }