Lambda2cov

The matrix <code>Lambda</code> is half the semivariogram matrix. The function
returns the conditional covariance with respect to entries in <code>co</code>,
restricted to the <code>subA</code> rows and the <code>subB</code> columns.

internal

Various tools for the analysis of univariate, multivariate and functional extremes. Exact simulation from max-stable processes [Dombry, Engelke and Oesting (2016) <doi:10.1093/biomet/asw008>, R-Pareto processes for various parametric models, including Brown-Resnick (Wadsworth and Tawn, 2014, <doi:10.1093/biomet/ast042>) and Extremal Student (Thibaud and Opitz, 2015, <doi:10.1093/biomet/asv045>). Threshold selection methods, including Wadsworth (2016) <doi:10.1080/00401706.2014.998345>, and Northrop and Coleman (2014) <doi:10.1007/s10687-014-0183-z>. Multivariate extreme diagnostics. Estimation and likelihoods for univariate extremes, e.g., Coles (2001) <doi:10.1007/978-1-4471-3675-0>.

Leo Belzile

Modelling of Extreme Values

Jennifer L. Wadsworth

Paul J. Northrop

Scott D. Grimshaw

Jin Zhang

Michael A. Stephens

Art B. Owen

Raphael Huser

Lambda2cov function

<dl><dt>Lambda</dt>
<dd>Negative definite matrix for the Huesler--Reiss model</dd>
<dt>co</dt>
<dd>vector of integer with conditioning sites</dd>
<dt>subA</dt>
<dd>vector of integers with sub-entries (not in <code>co</code>) for rows</dd>
<dt>subB</dt>
<dd>vector of integers with sub-entries (not in <code>co</code>) for columns. If missing, default to <code>subA</code>.</dd></dl>

Arguments

Transform variogram matrix to covariance of conditional random field — Lambda2cov

<dl>

<dt>Lambda</dt>
<dd>Negative definite matrix for the Huesler--Reiss model</dd>


<dt>co</dt>
<dd>vector of integer with conditioning sites</dd>


<dt>subA</dt>
<dd>vector of integers with sub-entries (not in <code>co</code>) for rows</dd>


<dt>subB</dt>
<dd>vector of integers with sub-entries (not in <code>co</code>) for columns. If missing, default to <code>subA</code>.</dd>

</dl>

Lambda2cov: Transform variogram matrix to covariance of conditional random field

Description

Usage

Arguments