decluster.runs {extRemes}R Documentation

Declustering Extremes

Description

Performs runs/intervals declustering.

Usage

decluster.runs(z, r)
decluster.intervals(z, ei)

Arguments

z Logical vector indicating which positions correspond to extreme values.
r Integer run length.
ei Estimate of the extremal index.

Details

Runs declustering: Extremes separated by fewer than `r' non-extremes belong to the same cluster. Setting `r' < 1 causes each extreme to form a separate cluster.

Intervals declustering: Extremes separated by fewer than `r' non-extremes belong to the same cluster, where `r' is the `nc'-th largest interexceedance time and `nc', the number of clusters, is estimated from the extremal index, `ei', and the times between extremes. Setting `ei' = 1 causes each extreme to form a separate cluster.

Value

A list containing

scheme Name of declustering scheme.
par Value of declustering parameter (i.e., run length).
nc Number of clusters.
size Vector of cluster sizes.
s Vector of times of extremes.
cluster Vector of numbers identifying clusters to which extremes belong.
t Vector of times between extremes.
inter Vector of intercluster time indicators (logical).
intra Vector of intracluster time indicators (logical).

Note

Maintained by Eric Gilleland.

Author(s)

Chris Ferro

References

Smith RL (1989) Extreme value analysis of environmental time series: an application to trend detection in ground-level ozone. Statistical Science 4, 367-393.

Ferro CAT and Segers J (2003) Inference for clusters of extreme values. Journal of the Royal Statistical Society B 65, 545-556.

See Also

exi.intervals

Examples

# Simulate a dependent series of random variables.
x <- runif(1000,-1,1)
x[2:1000] <- x[1:999]*0.6
# -- DON'T RUN
# pacf( x)

# use runs and intervals declustering using the 90th percentile as the threshold.
u <- quantile(x, 0.9)
z <- x > u
exi.intervals(z)
tmp1 <- decluster.runs(z, 1)
tmp2 <- decluster.intervals( z, exi.intervals(z))

[Package extRemes version 1.59 Index]