Decluster Point Process

Description

Declusters clustered point process data so that Poisson assumption is more tenable over a high threshold.

Usage

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decluster(series, run = NA, picture = TRUE)

Arguments

series

a numeric vector of threshold exceedances with a times attribute which should be a numeric vector containing either the indices or the times/dates of each exceedance (if times/dates, the attribute should be an object of class "POSIXct" or an object that can be converted to that class; see as.POSIXct)

run

parameter to be used in the runs method; any two consecutive threshold exceedances separated by more than this number of observations/days are considered to belong to different clusters

picture

whether or not a picture of declustering should be drawn

Value

The declustered object.

References

Embrechts, P., Klueppelberg, C., Mikosch, T. (1997). Modelling Extremal Events. Springer. Chapter 8, 413–429.

See Also

pot, exindex, as.POSIXct

Examples

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# decluster the 200 exceedances of a particular threshold in 
# the negative BMW data
data(bmw)
out <- pot(-bmw, ne = 200) 
decluster(out$data, 30)