mexRangeFit: Estimate dependence parameters in a conditional multivariate extreme values model over a range of thresholds.

Description

Diagnostic tool to aid the choice of threshold to be used for the estimation of the dependence parameters in the conditional multivariate extreme values model of Heffernan and Tawn, 2004.

Usage

mexRangeFit(x, which, quantiles = seq(0.5, 0.9, length = 9), start=c(.01, .01), R = 10, nPass=3, trace=10, margins = "laplace", constrain = TRUE, v = 10)

Arguments

An object of class mex or migpd.

which

The variable on which to condition.

quantiles

A numeric vector specifying the quantiles of the marginal distribution of the conditioning variable at which to fit the dependence model.

start

See documentation for this argument in mexDependence.

The number of bootstrap runs to perform at each threshold. Defaults to R=10.

nPass

Argument passed to function bootmex.

trace

Argument passed to function bootmex.

margins

Argument passed to function mexDependence.

constrain

Argument passed to function mexDependence.

...

Further graphical parameters may be passed, which will be used for plotting.

Value

NULL.

Details

Dependence model parameters are estimated using a range of threshold values. The sampling variability of these estimates is characterised using the bootstrap. Point estimates and bootstrap estimates are finally plotted over the range of thresholds. Choice of threshold should be made such that the point estimates at the chosen threshold and beyond are constant, up to sampling variation.

References

J. E. Heffernan and J. A. Tawn, A conditional approach for multivariate extreme values, Journal of the Royal Statistical society B, 66, 497 -- 546, 2004

Examples

Run this code

# Example commented out to reduce R CMD check time
#  w <- migpd(winter, mqu=.7)
#  w
#  par(mfrow=c(4,2))
#  mexRangeFit(w,which=1,main="Winter data, Heffernan and Tawn 2004",cex=0.5)

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