Learn R Programming

evir (version 1.7-4)

decluster: Decluster Point Process

Description

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

Usage

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

Run this code
# NOT RUN {
# decluster the 200 exceedances of a particular threshold in 
# the negative BMW data
data(bmw)
out <- pot(-bmw, ne = 200) 
decluster(out$data, 30) 
# }

Run the code above in your browser using DataLab