On generalized elliptical quantiles in the nonlinear quantile regression setup

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F15%3A10314011" target="_blank" >RIV/00216208:11320/15:10314011 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/67985556:_____/15:00434510

Výsledek na webu

<a href="http://dx.doi.org/10.1007/s11749-014-0405-3" target="_blank" >http://dx.doi.org/10.1007/s11749-014-0405-3</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s11749-014-0405-3" target="_blank" >10.1007/s11749-014-0405-3</a>

Jazyk výsledku

angličtina

Název v původním jazyce

On generalized elliptical quantiles in the nonlinear quantile regression setup

Popis výsledku v původním jazyce

Inspired by nonlinear quantile regression, the article introduces, investigates, discusses, and illustrates a new concept of generalized elliptical location quantiles. They may require less stringent moment assumptions, be less sensitive to outliers, beless rigid, employ more a priori information regarding the location of the distribution, and have higher potential for various regression generalizations than their common elliptical predecessor defined in the convex optimization framework by means of standard linear quantile regression. Furthermore, they still include an equivalent of their predecessor as a special case and inherit most of its favorable features such as the probability interpretation, natural equivariance properties, and good behaviorfor elliptical and symmetric distributions, which is demonstrated both by theoretical results and data examples with convincing graphical output. On the other hand, the new elliptical quantiles need not always be uniquely defined and they

Název v anglickém jazyce

On generalized elliptical quantiles in the nonlinear quantile regression setup

Popis výsledku anglicky

Inspired by nonlinear quantile regression, the article introduces, investigates, discusses, and illustrates a new concept of generalized elliptical location quantiles. They may require less stringent moment assumptions, be less sensitive to outliers, beless rigid, employ more a priori information regarding the location of the distribution, and have higher potential for various regression generalizations than their common elliptical predecessor defined in the convex optimization framework by means of standard linear quantile regression. Furthermore, they still include an equivalent of their predecessor as a special case and inherit most of its favorable features such as the probability interpretation, natural equivariance properties, and good behaviorfor elliptical and symmetric distributions, which is demonstrated both by theoretical results and data examples with convincing graphical output. On the other hand, the new elliptical quantiles need not always be uniquely defined and they

Druh

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

CEP obor

BA - Obecná matematika

OECD FORD obor

—

Projekt

<a href="/cs/project/GA14-07234S" target="_blank" >GA14-07234S: Mnohorozměrné regresní kvantily v ekonometrii</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

Test

ISSN

1133-0686

e-ISSN

—

Svazek periodika

24

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

ES - Španělské království

Počet stran výsledku

16

Strana od-do

249-264

Kód UT WoS článku

000354714100004

EID výsledku v databázi Scopus

2-s2.0-84929837079