Orthogonal decomposition of multivariate densities in Bayes spaces and relation with their copula-based representation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F23%3A73622503" target="_blank" >RIV/61989592:15310/23:73622503 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0047259X2300074X" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0047259X2300074X</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jmva.2023.105228" target="_blank" >10.1016/j.jmva.2023.105228</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Orthogonal decomposition of multivariate densities in Bayes spaces and relation with their copula-based representation

Popis výsledku v původním jazyce

Bayes spaces were initially designed to provide a geometric framework for the modeling and analysis of distributional data. It has recently come to light that this methodology can be exploited to construct an orthogonal decomposition of a bivariate probability density into an independence and an interaction part. In this paper, new insights into these results are given by reformulating them using Hilbert space theory, and a multivariate extension is developed using a distributional analog of the Hoeffding- Sobol identity. A connection is also made between the resulting decomposition of a multivariate density and its copula-based representation.

Název v anglickém jazyce

Orthogonal decomposition of multivariate densities in Bayes spaces and relation with their copula-based representation

Popis výsledku anglicky

Bayes spaces were initially designed to provide a geometric framework for the modeling and analysis of distributional data. It has recently come to light that this methodology can be exploited to construct an orthogonal decomposition of a bivariate probability density into an independence and an interaction part. In this paper, new insights into these results are given by reformulating them using Hilbert space theory, and a multivariate extension is developed using a distributional analog of the Hoeffding- Sobol identity. A connection is also made between the resulting decomposition of a multivariate density and its copula-based representation.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/GF22-15684L" target="_blank" >GF22-15684L: Zobecněná relativní data a robustnost v Bayesových prostorech</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

JOURNAL OF MULTIVARIATE ANALYSIS

ISSN

0047-259X

e-ISSN

1095-7243

Svazek periodika

198

Číslo periodika v rámci svazku

NOV

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

24

Strana od-do

"105228-1"-"105228-24"

Kód UT WoS článku

001069280800001

EID výsledku v databázi Scopus

2-s2.0-85167584724