svd.tpdm

Calculates singular value decomposition (SVD) of given cross-TPDM

An implementation of
1) the tail pairwise dependence matrix (TPDM) as described in Jiang & Cooley (2020) <doi:10.1175/JCLI-D-19-0413.1>
2) the extremal pattern index (EPI) as described in Szemkus & Friederichs ('Spatial patterns and indices for heatwave and droughts over Europe using a decomposition of extremal dependency'; submitted to ASCMO 2023).

Svenja Szemkus

ExtrPatt

Spatial Dependencies and Indices for Extremes

Dan Cooley

Yuing Jiang

svd.tpdm function

<dl><dt>Sigma</dt>
<dd>A n x n data array, containing the cross-TPDM, can be output of est.tpdm.</dd>
<dt>X</dt>
<dd>A t x n dimensional, numeric Data-matrix with t: Number of time steps and n: Number of grid points/stations.</dd>
<dt>Y</dt>
<dd>Same as X but for second variable.</dd></dl>

Arguments

Singular Value decomposition for cross-TPDM — svd.tpdm

<dl>

<dt>Sigma</dt>
<dd>A n x n data array, containing the cross-TPDM, can be output of est.tpdm.</dd>


<dt>X</dt>
<dd>A t x n dimensional, numeric Data-matrix with t: Number of time steps and n: Number of grid points/stations.</dd>


<dt>Y</dt>
<dd>Same as X but for second variable.</dd>

</dl>

svd.tpdm: Singular Value decomposition for cross-TPDM

Description

Usage

Value

Arguments