evmBoot

summary.evmBoot

plot.evmBoot

coef.evmBoot

print.summary.evmBoot

print.evmBoot

This runs a parametric bootstrap simulating from an optimized
model.

Statistical extreme value modelling of threshold excesses, maxima
and multivariate extremes. Univariate models for threshold excesses and maxima
are the Generalised Pareto, and Generalised Extreme Value model respectively.
These models may be fitted by using maximum (optionally penalised-)likelihood,
or Bayesian estimation, and both classes of models may be fitted with covariates
in any/all model parameters. Model diagnostics support the fitting process.
Graphical output for visualising fitted models and return level estimates is
provided. For serially dependent sequences, the intervals declustering algorithm
of Ferro and Segers (2003) <doi:10.1111/1467-9868.00401> is provided, with
diagnostic support to aid selection of threshold and declustering horizon.
Multivariate modelling is performed via the conditional approach of Heffernan
and Tawn (2004) <doi:10.1111/j.1467-9868.2004.02050.x>, with graphical tools for
threshold selection and to diagnose estimation convergence.

Harry Southworth

texmex

Statistical Modelling of Extreme Values

Yiannis Papastathopoulos

Alec Stephenson

Stuart Coles

evmBoot function

<dl><dt>o</dt>
<dd>a fit <code>evmOpt</code> object</dd>
<dt>R</dt>
<dd>the number of parametric bootstrap samples to run</dd>
<dt>trace</dt>
<dd>the frequency of trace messages</dd>
<dt>cores</dt>
<dd>The number of coresto use when bootstrapping. Defaults
to <code>cores=NULL</code> and the function guesses how many cores
are available and uses them all.</dd>
<dt>export</dt>
<dd>Character vector of names of variables to export. See the
help file for <code>parallel::export</code>. Defaults to <code>export = NULL</code>
and most users will never need to use it.</dd>
<dt>theCall</dt>
<dd>(for internal use)</dd>
<dt>x</dt>
<dd>an <code>evmBoot</code> object</dd>
<dt>col</dt>
<dd>colour used to fill histogram</dd>
<dt>border</dt>
<dd>the colour of the border around the bars</dd>
<dt>object</dt>
<dd>a <code>evmBoot</code> object</dd>
<dt>...</dt>
<dd>other arguments passed to internal functions</dd></dl>

Arguments

Bootstrap an evmOpt fit — evmBoot

<dl>

<dt>o</dt>
<dd>a fit <code>evmOpt</code> object</dd>


<dt>R</dt>
<dd>the number of parametric bootstrap samples to run</dd>


<dt>trace</dt>
<dd>the frequency of trace messages</dd>


<dt>cores</dt>
<dd>The number of coresto use when bootstrapping. Defaults
to <code>cores=NULL</code> and the function guesses how many cores
are available and uses them all.</dd>


<dt>export</dt>
<dd>Character vector of names of variables to export. See the
help file for <code>parallel::export</code>. Defaults to <code>export = NULL</code>
and most users will never need to use it.</dd>


<dt>theCall</dt>
<dd>(for internal use)</dd>


<dt>x</dt>
<dd>an <code>evmBoot</code> object</dd>


<dt>col</dt>
<dd>colour used to fill histogram</dd>


<dt>border</dt>
<dd>the colour of the border around the bars</dd>


<dt>object</dt>
<dd>a <code>evmBoot</code> object</dd>


<dt>...</dt>
<dd>other arguments passed to internal functions</dd>

</dl>

Bootstrap an evmOpt fit

evmBoot: Bootstrap an evmOpt fit

Description

Usage

Value

Arguments

See Also