stdf

stdf.Network

stdf.HRMtree

stdf.HRMBG

Computes the stable tail dependence function for given coordinates. If object of class <code>Network</code> or
 its subclasses is passed
non-parametric estimates of the stdf are computed. If an object of class <code>HRMtree</code> or <code>HRMBG</code> is passed
parametric estimates are computed with parameters that constitute the slot <code>$depParams</code> in the object.

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

stdf function

<dl><dt>obj</dt>
<dd>Object of class <code>Network</code>, or <code>HRMtree</code> or <code>HRMBG</code></dd>
<dt>...</dt>
<dd>additional arguments</dd>
<dt>Y</dt>
<dd>A matrix of evaluation points with columns named according to the names of the nodes with
observed variables,
and of dimensions qx|U| where U is the set of observed variables, and q is the number of vectors at which the
stdf is evaluated.</dd>
<dt>k_ratio</dt>
<dd>the ration of the upper order statistics as a share of the size of the sample</dd>
<dt>x</dt>
<dd>Vector of evaluation points with named elements according to the nodes of the graph.</dd>
<dt>Ubar</dt>
<dd>The set of nodes for which data are missing. It should stay at its default value NULL.</dd></dl>

Arguments

Stable tail dependence function (stdf) — stdf

<dl>

<dt>obj</dt>
<dd>Object of class <code>Network</code>, or <code>HRMtree</code> or <code>HRMBG</code></dd>


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


<dt>Y</dt>
<dd>A matrix of evaluation points with columns named according to the names of the nodes with
observed variables,
and of dimensions qx|U| where U is the set of observed variables, and q is the number of vectors at which the
stdf is evaluated.</dd>


<dt>k_ratio</dt>
<dd>the ration of the upper order statistics as a share of the size of the sample</dd>


<dt>x</dt>
<dd>Vector of evaluation points with named elements according to the nodes of the graph.</dd>


<dt>Ubar</dt>
<dd>The set of nodes for which data are missing. It should stay at its default value NULL.</dd>

</dl>

stdf: Stable tail dependence function (stdf)

Description

Usage

Value

Arguments

Examples