# rbvgpd: Parametric Bivariate GPD In POT: Generalized Pareto Distribution and Peaks Over Threshold

 bvgpd R Documentation

## Parametric Bivariate GPD

### Description

Density, distribution function and random generation for six different parametric bivariate GPD

### Usage

```rbvgpd(n, alpha, model = "log", asCoef, asCoef1, asCoef2, mar1 =
c(0,1,0), mar2 = mar1)
pbvgpd(q, alpha, model = "log", asCoef, asCoef1, asCoef2, mar1 =
c(0,1,0), mar2 = mar1, lower.tail = TRUE)
```

### Arguments

 `n` The number of observations to be simulated. `q` A matrix or vector with two columns at which the distribution is computed. `alpha` Dependence parameter for the logistic, asymmetric logistic, negative logistic, asymmetric negative logistic, mixed 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. `asCoef,asCoef1,asCoef2` The asymmetric coefficients for the asymmetric logistic, asymmetric negative logistic and asymmetric mixed models. `mar1,mar2` Vectors of length 3 giving the marginal parameters. `lower.tail` Logical. If `TRUE` (the default), P[X <= x] is computed, else P[X >= x].

### Details

The logistic and asymmetric logistic models respectively are simulated using bivariate versions of Algorithms 1.1 and 1.2 in Stephenson(2003). All other models are simulated using a root finding algorithm to simulate from the conditional distributions.

### Value

Generate a random vector of length `n`.

### Author(s)

Mathieu Ribatet (Alec Stephenson for the C codes)

### References

Stephenson, A. G. (2003) Simulating multivariate extreme value distributions of logistic type. Extremes, 6(1), 49–60.

### Examples

```x <- rbvgpd(1000, alpha = 0.25, model = "log", mar1 = c(0,1,0.25), mar2
= c(2,0.5, -0.15))
y <- rbvgpd(1000, alpha = 0.75, model = "nlog", mar1 = c(0,1,0.25), mar2
= c(2,0.5, -0.15))
par(mfrow=c(1,2))
plot(x);plot(y)
```

POT documentation built on April 14, 2022, 5:07 p.m.