# concprob: Pairwise empirical and extremal concurrence probabilities In SpatialExtremes: Modelling Spatial Extremes

## Description

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

## Usage

 ```1 2 3 4``` ```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.

Mathieu Ribatet

## References

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

`fmadogram`, `lmadogram`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```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 = 1.75) ##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) ```

### Example output  ```
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SpatialExtremes documentation built on May 2, 2019, 5:45 p.m.