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