J 2020

Hierarchical Archimedean Copulas for MATLAB and Octave: The HACopula Toolbox

GÓRECKI, Jan, Marius HOFERT a Martin HOLEŇA

Základní údaje

Originální název

Hierarchical Archimedean Copulas for MATLAB and Octave: The HACopula Toolbox

Autoři

GÓRECKI, Jan (203 Česká republika, garant, domácí), Marius HOFERT (124 Kanada) a Martin HOLEŇA (203 Česká republika)

Vydání

Journal of Statistical Software, 2020, 1548-7660

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Kód RIV

RIV/47813059:19520/20:A0000145

Organizační jednotka

Obchodně podnikatelská fakulta v Karviné

DOI

http://dx.doi.org/10.18637/jss.v093.i10

UT WoS

000542224700001

Klíčová slova anglicky

copula; hierarchical Archimedean copula; structure; family; estimation; collapsing; sampling; goodness-of-fit; Kendall’s tau; tail dependence; MATLAB; Octave
Změněno: 7. 5. 2021 11:47, Ing. Jan Górecki, Ph.D.

Anotace

V originále

To extend the current implementation of copulas in MATLAB to non-elliptical distributions in arbitrary dimensions enabling for asymmetries in the tails, the toolbox HACopula provides functionality for modeling with hierarchical (or nested) Archimedean copulas. This includes their representation as MATLAB objects, evaluation, sampling, estimation and goodness-of-fit testing, as well as tools for their visual representation or computation of corresponding matrices of Kendall's tau and tail dependence coefficients. These are first presented in a quick-and-simple manner and then elaborated in more detail to show the full capability of HACopula. As an example, sampling, estimation and goodness-of-fit of a 100-dimensional hierarchical Archimedean copula is presented, including a speed up of its computationally most demanding part. The toolbox is also compatible with Octave, where no support for copulas in more than two dimensions is currently provided.
Zobrazeno: 24. 11. 2024 20:00