R: Pairwise empirical and extremal concurrence probabilities

concprob {SpatialExtremes} | R Documentation

## Pairwise empirical and extremal concurrence probabilities

### Description

This function computes the pairwise empirical or the pairwise extremal concurrence probability estimates.

### Usage

    concprob(data, coord, fitted, n.bins, add = FALSE, xlim = c(0,
    max(dist)), ylim = c(min(0, concProb), max(1, concProb)), col = 1:2,
    which = "kendall", xlab, ylab, block.size = floor(nrow(data)^(1/3)),
    plot = TRUE, compute.std.err = FALSE, ...)

### Arguments

`data` | A matrix representing the data. Each column corresponds to one location.
`coord` | A matrix that gives the coordinates of each location. Each row corresponds to one location.
`fitted` | An object of class maxstab - usually the output of the `fitmaxstab` function. May be missing.
`n.bins` | The number of bins to be used. If missing, pairwise F-madogram estimates will be computed.
`xlim,ylim` | A numeric vector of length 2 specifying the x/y coordinate ranges.
`col` | The colors used for the points and optionnaly the fitted curve.
`which` | A character string specifying which estimator should be used. Should be one of "emp" (empirical), "boot" (bootstrap version) and "kendall" (kendall based).
`xlab,ylab` | The labels for the x/y-axis (may be missing).
`add` | Logical. If `TRUE`, the plot is added to the current figure; otherwhise (default) a new plot is computed.
`block.size` | Integer specifying the block size for the empirical and bootstrap estimator.
`plot` | Logical. If `TRUE` (default) a plot is produced.
`compute.std.err` | Logical. If `TRUE`, standard errors are estimated using a jackknife procedure. It is currently only available for the Kendall estimator.
`...` | Additional options to be passed to the `plot` function.

### Value

This function returns invisibly a matrix containing the pairwise distances and the concurrence probability estimates.

### Author(s)

Mathieu Ribatet

### References

Dombry, C., Ribatet, M. and Stoev, S. (2017) Probabilities of concurrent extremes. To appear in JASA

### See Also

`fmadogram`, `lmadogram`

### Examples

    n.site <- 25
    locations <- matrix(runif(2*n.site, 0, 10), ncol = 2)
    colnames(locations) <- c("lon", "lat")

    ##Simulate a max-stable process - with unit Frechet margins
    n.obs <- 100
    data <- rmaxstab(n.obs, locations, cov.mod = "whitmat", nugget = 0, range = 1,
    smooth = 2)

    ##Compute the F-madogram
    concprob(data, locations)

    ##Compare the F-madogram with a fitted max-stable process
    fitted <- fitmaxstab(data, locations, "whitmat", nugget = 0)
    concprob(fitted = fitted)

[Package SpatialExtremes version 2.0-5 Index]