depmeasure

is.depmeasure

summary.depmeasure

plot.depmeasure

print.depmeasure

Test or show objects of class "depmeasure".

classes

Characterisation of the extremal dependence structure of time series, avoiding pre-processing and filtering as done typically with peaks-over-threshold methods. It uses the conditional approach of Heffernan and Tawn (2004) <DOI:10.1111/j.1467-9868.2004.02050.x> which is very flexible in terms of extremal and asymptotic dependence structures, and Bayesian methods improve efficiency and allow for deriving measures of uncertainty. For example, the extremal index, related to the size of clusters in time, can be estimated and samples from its posterior distribution obtained.

Thomas Lugrin

tsxtreme

Bayesian Modelling of Extremal Dependence in Time Series

depmeasure function

<dl> <dt>x</dt>
<dd>an arbitrary R object.</dd></dl>

Arguments

Dependence measures estimates — depmeasure

<dl>

 <dt>x</dt>
<dd>an arbitrary R object.</dd>

</dl>

depmeasure: Dependence measures estimates

Description

Usage

Value

Arguments

See Also