Independence tests based on the conditional expectation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F15%3A86094761" target="_blank" >RIV/61989100:27510/15:86094761 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Independence tests based on the conditional expectation

Popis výsledku v původním jazyce

In this paper we propose a new procedure for testing independence of random variables, which is based on the conditional expectation. As it is well known, the behaviour of the conditional expectation may determine a necessary condition for stochastic independence, that is, the so called mean independence. We provide a necessary and sufficient condition for independence in terms of conditional expectation and propose an alternative method to test independence based on this result. Consequently, we provide general class of tests. Observe that generally some non-parametric methods are needed to approximate the conditional expectation, since its exact expression (given the joint distribution) is usually unknown, except for few trivial cases (e.g. Gaussian): we generalize this well known result to the family of elliptical distributions. In order to obtain a sufficiently accurate approximation of the conditional expectation, we propose to use the kernel method or, alternatively, the recently

Název v anglickém jazyce

Independence tests based on the conditional expectation

Popis výsledku anglicky

In this paper we propose a new procedure for testing independence of random variables, which is based on the conditional expectation. As it is well known, the behaviour of the conditional expectation may determine a necessary condition for stochastic independence, that is, the so called mean independence. We provide a necessary and sufficient condition for independence in terms of conditional expectation and propose an alternative method to test independence based on this result. Consequently, we provide general class of tests. Observe that generally some non-parametric methods are needed to approximate the conditional expectation, since its exact expression (given the joint distribution) is usually unknown, except for few trivial cases (e.g. Gaussian): we generalize this well known result to the family of elliptical distributions. In order to obtain a sufficiently accurate approximation of the conditional expectation, we propose to use the kernel method or, alternatively, the recently

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

WSEAS Transactions on Mathematics

ISSN

1109-2769

e-ISSN

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Svazek periodika

14

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

10

Strana od-do

335-344

Kód UT WoS článku

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EID výsledku v databázi Scopus

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