# qqgev: QQ-plot for the GEV parameters In SpatialExtremes: Modelling Spatial Extremes

## Description

This function compares the GEV parameters estimated separately for each location to the ones estimated from a fitted spatial model.

## Usage

 `1` ```qqgev(fitted, xlab, ylab, ...) ```

## Arguments

 `fitted` An object of class `maxstab` or `spatgev`. Most often, this will be the output of `fitmaxstab`, `fitcovmat`, `fitcovariance` or `fitspatgev`. `xlab,ylab` The x and y-axis labels. May be missing. `...` Optional arguments to be passed to the `plot` function.

A QQ-plot.

Mathieu Ribatet

## References

Schlather, M. (2002) Models for Stationary Max-Stable Random Fields. Extremes 5:1, 33–44.

Schlather, M. and Tawn, J. A. (2003) A dependence measure for multivariate and spatial extreme values: Properties and inference. Biometrika 90(1):139–156.

Smith, R. L. (1990) Max-stable processes and spatial extremes. Unpublished manuscript.

`qqextcoeff`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29``` ```##Define the coordinate of each location n.site <- 30 locations <- matrix(runif(2*n.site, 0, 10), ncol = 2) colnames(locations) <- c("lon", "lat") ##Simulate a max-stable process - with unit Frechet margins data <- rmaxstab(50, locations, cov.mod = "gauss", cov11 = 100, cov12 = 25, cov22 = 220) ##Now define the spatial model for the GEV parameters param.loc <- -10 + 2 * locations[,2] param.scale <- 5 + 2 * locations[,1] + locations[,2]^2 param.shape <- rep(0.2, n.site) ##Transform the unit Frechet margins to GEV for (i in 1:n.site) data[,i] <- frech2gev(data[,i], param.loc[i], param.scale[i], param.shape[i]) ##Define a model for the GEV margins to be fitted ##shape ~ 1 stands for the GEV shape parameter is constant ##over the region loc.form <- loc ~ lat scale.form <- scale ~ lon + I(lat^2) shape.form <- shape ~ 1 fitted <- fitspatgev(data, locations, loc.form = loc.form, scale.form = scale.form, shape.form = shape.form) qqgev(fitted) ```

SpatialExtremes documentation built on Jan. 5, 2018, 3 p.m.