Podrobný výpis o publikaci

GÓRECKI, Jan, Marius HOFERT a Martin HOLEŇA. Hierarchical Archimedean Copulas for MATLAB and Octave: The HACopula Toolbox. Journal of Statistical Software. 2020, roč. 93, č. 10, s. 1-36. ISSN 1548-7660. Dostupné z: https://dx.doi.org/10.18637/jss.v093.i10.

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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
Originální 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
WWW	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
Změnil	Změnil: Ing. Jan Górecki, Ph.D., učo 49432. Změněno: 7. 5. 2021 11:47.

Anotace
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.

Anotace

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.