Calculates maximum likelihood estimates of the extremal index \(\theta\) based on the \(K\)-gaps model for threshold inter-exceedances times of Suveges and Davison (2010).
kgaps(data, u, k = 1, inc_cens = FALSE)
A numeric vector of raw data. No missing values are allowed.
A numeric scalar. Extreme value threshold applied to data.
A numeric scalar. Run parameter \(K\), as defined in Suveges and
Davison (2010). Threshold inter-exceedances times that are not larger
than k
units are assigned to the same cluster, resulting in a
\(K\)-gap equal to zero. Specifically, the \(K\)-gap \(S\)
corresponding to an inter-exceedance time of \(T\) is given by
\(S = \max(T - K, 0)\).
A logical scalar indicating whether or not to include contributions from censored inter-exceedance times relating to the first and last observation. See Attalides (2015) for details.
An object (a list) of class c("kgaps", "exdex")
containing
theta
The maximum likelihood estimate (MLE) of \(\theta\).
se
The estimated standard error of the MLE.
ss
The list of summary statistics returned from
kgaps_stat
.
k, u, inc_cens
The input values of k
,
u
and inc_cens
.
call
The call to kgaps
.
The maximum likelihood estimate of the extremal index \(\theta\)
under the \(K\)-gaps model of Suveges and Davison (2010) is calculated.
If inc_cens = TRUE
then information from censored inter-exceedance
times is included in the likelihood to be maximized, following
Attalides (2015). The form of the log-likelihood is given in the
Details section of kgaps_stat
.
It is possible that the estimate of \(\theta\) is equal to 1, and also
possible that it is equal to 0. kgaps_stat
explains the
respective properties of the data that cause these events to occur.
Suveges, M. and Davison, A. C. (2010) Model misspecification in peaks over threshold analysis, The Annals of Applied Statistics, 4(1), 203-221. https://doi.org/10.1214/09-AOAS292
Attalides, N. (2015) Threshold-based extreme value modelling, PhD thesis, University College London. http://discovery.ucl.ac.uk/1471121/1/Nicolas_Attalides_Thesis.pdf
confint.kgaps
to estimate confidence intervals
for \(\theta\).
kgaps_imt
for the information matrix test, which
may be used to inform the choice of the pair (u, k
).
choose_uk
for a diagnostic plot based on
kgaps_imt
.
kgaps_stat
for the calculation of sufficient
statistics for the \(K\)-gaps model.
kgaps_post
in the
revdbayes
package for Bayesian inference
about \(\theta\) using the \(K\)-gaps model.
spm
for estimation of the extremal index
\(\theta\) using a semiparametric maxima method.
iwls
: iterated weighted least squares estimator.
# NOT RUN {
### S&P 500 index
u <- quantile(sp500, probs = 0.60)
theta <- kgaps(sp500, u)
theta
summary(theta)
### Newlyn sea surges
u <- quantile(newlyn, probs = 0.60)
theta <- kgaps(newlyn, u, k= 2)
theta
summary(theta)
# }
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