Package 'extRemes' - What are R and CRAN?

30 extremalindex
extremalindex
Extemal Index
Description
Estimate the extremal index.
Usage
extremalindex(x, threshold, method = c("intervals", "runs"), run.length = 1,
na.action = na.fail, ...)
## S3 method for class extremalindex
ci(x, alpha = 0.05, R = 502, return.samples = FALSE, ...)
## S3 method for class extremalindex
print(x, ...)
Arguments
x
threshold
method
run.length
na.action
alpha
R
Details
A data vector.
ci and print: output from extremalindex.
numeric of length one or the length of x giving the value above which (noninclusive)
the extremal index should be calculated.
character string stating which method should be used to estimate the extremal
index.
For runs declustering only, an integer giving the number of threshold deficits to
be considered as starting a new cluster.
funciton to handle missing values.
number between zero and one giving the (1 - alpha) * 100 percent confidence
level. For example, alpha = 0.05 corresponds to 95 percent confidence; alpha is
the significance level (or probability of type I errors) for hypothesis tests based
on the CIs.
Number of replicate samples to use in the bootstrap procedure.
return.samples logical; if TRUE, the bootstrap replicate samples will be returned instead of CIs.
This is useful, for example, if one wishes to find CIs using a better method than
the one used here (percentile method).
... optional arguments to decluster. Not used by ci or print.
The extremal index is a useful indicator of how much clustering of exceedances of a threshold
occurs in the limit of the distribution. For independent data, theta = 1, (though the converse is does
not hold) and if theta < 1, then there is some dependency (clustering) in the limit.