extremal.index: Extremal index estimation

In theGreatWhiteShark/climex: Estimating Extreme Events in Climatic Time Series (using Data of the DWD)

Extremal index estimation

Description

Estimates the extremal index of a time series.

Usage

extremal.index(x, threshold, silent = FALSE)

Arguments

x	Time series of class xts or numerical.
threshold	Only events exceeding a specific threshold will be considered extreme events and thus will be subject of the declustering.
silent	Whether or not to display warnings.

Details

The extremal index can be thought of as the inverse of the mean cluster size. It can be calculated by the blocks method of Ferro and Segers, 2003. I will use the bias-free estimator provided in equation (4) in their paper. This one is supposed to be the most robust one and is relying on a moment estimation.

Another way to estimate it, would be using the runs method as in Stuart Coles (2001). But therefore one had to know the minimal distance between the clusters first. Since the whole point of this function to estimate exactly this quantity for its use in the decluster function, I don't see the point of implementing this method too.

Value

Numerical vector containing c( extremal index, number of clusters, minimal distance between clusters (minimal.distance))

Author(s)

Philipp Mueller

See Also

Other extremes: block.list, block.xts, block, decluster.list, decluster.xts, decluster, gev.density, gpd.density, qevd, return.level.climex.fit.gev, return.level.climex.fit.gpd, return.level.list, return.level.numeric, return.level, revd, rlevd, threshold.list, threshold.xts, threshold, upper.limit.climex.fit.gev, upper.limit.climex.fit.gpd, upper.limit.list, upper.limit.numeric, upper.limit

theGreatWhiteShark/climex documentation built on July 13, 2022, 9:11 a.m.