subset

Provides tools for estimation of edge weights on graphical models with respect to trees and block graphs and parameterized by a particular family of max-stable copulas. The edge weights are parameters of tail dependence between adjacent variables and these edge weights determine the joint tail dependence between all variables in the context of a particular parametric model. For methods of moment estimator, composite likelihood estimator please see Asenova et al. (2021) <doi:10.1007/s10687-021-00407-5>. For estimation based on extremal coefficients see Asenova et al. (2021) as well as Einmahl et al. (2016) <doi:10.2139/ssrn.2717531>. For cliquewise estimation please see Engelke and Hitz (2020) <doi:10.1111/rssb.12355>.

Stefka Asenova

gremes

Estimation of Tail Dependence in Graphical Models

subset function

<dl><dt>obj</dt>
<dd>object of appropriate class</dd>
<dt>...</dt>
<dd>additional arguments</dd></dl>

Arguments

For description and examples of the method applied on objects of class <code>FlowConnect</code>.

See <code>subset.FlowConnect</code>

For description and examples of the method applied on objectobjects of class <code>Neighborhood</code>.

See <code>subset.Neighborhood</code>

Generic for subset — subset

<dl>

<dt>obj</dt>
<dd>object of appropriate class</dd>


<dt>...</dt>
<dd>additional arguments</dd>

</dl>

For description and examples of the method applied on objects of class <code>FlowConnect</code>.

For description and examples of the method applied on objectobjects of class <code>Neighborhood</code>.

subset: Generic for `subset`

Description

Usage

Value

Arguments

See <code>subset.FlowConnect</code>

See <code>subset.Neighborhood</code>