R: Calculate Conditional Copulas for Parametric Bivariate...

ccbvevd {evd} | R Documentation

## Calculate Conditional Copulas for Parametric Bivariate Extreme Value Distributions

### Description

Conditional copula functions, conditioning on either margin, for nine parametric bivariate extreme value models.

### Usage

    ccbvevd(x, mar = 2, dep, asy = c(1, 1), alpha, beta, model = c("log",
        "alog", "hr", "neglog", "aneglog", "bilog", "negbilog", "ct",
        "amix"), lower.tail = TRUE)

### Arguments

`x` | A matrix or data frame, ordinarily with two columns, which may contain missing values. A data frame may also contain a third column of mode `logical`, which itself may contain missing values (see Details).
`mar` | One or two; conditions on this margin.
`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. If parameter arguments are given that do not correspond to the specified model those arguments are ignored, with a warning.
`lower.tail` | Logical; if `TRUE` (default), the conditional distribution function is returned; the conditional survivor function is returned otherwise.

### Details

The function calculates P(U1 < x1|U2 = x2), where (U1,U2) is a random vector with Uniform(0,1) margins and with a dependence structure given by the specified parametric model. By default, the values of x1 and x2 are given by the first and second columns of the argument `x`. If `mar = 1` then this is reversed.

If `x` has a third column x3 of mode logical, then the function returns P(U1 < x1|U2 = x2,I = x3), according to inference proceedures derived by Stephenson and Tawn (2004). See `fbvevd`. This requires numerical integration, and hence will be slower.

This function is mainly for internal use. It is used by `plot.bvevd` to calculate the conditional P-P plotting diagnostics.

### Value

A numeric vector of probabilities.

### References

Stephenson, A. G. and Tawn, J. A. (2004) Exploiting Occurence Times in Likelihood Inference for Componentwise Maxima. Biometrika 92(1), 213–217.

### See Also

`rbvevd`, `fbvevd`, `plot.bvevd`

[Package evd version 2.3-5 Index]