evmc {evd} | R Documentation

## 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 eight parametric bivariate extreme value distributions.

### Usage

    evmc(n, dep, asy = c(1,1), alpha, beta, model = "log",
        margins = "uniform")

### 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 and Coles-Tawn models.
`model` | The specified model; a character string. Must be either `"log"` (the default), `"alog"`, `"hr"`, `"neglog"`, `"aneglog"`, `"bilog"`, `"negbilog"` or `"ct"` (or any unique partial match), for the logistic, asymmetric logistic, Husler-Reiss, negative logistic, asymmetric negative logistic, bilogistic, negative bilogistic and Coles-Tawn 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), `"exponential"`, `"frechet"` or `"gumbel"` (or any unique partial match), for the uniform, standard exponential, 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 = "exp")

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