The Process Induced by Slope Components of α-Regression Quantile

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F24%3A00600155" target="_blank" >RIV/67985556:_____/24:00600155 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-031-61853-6_12" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-61853-6_12</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-61853-6_12" target="_blank" >10.1007/978-3-031-61853-6_12</a>

Jazyk výsledku

angličtina

Název v původním jazyce

The Process Induced by Slope Components of α-Regression Quantile

Popis výsledku v původním jazyce

We consider the linear regression model, along with the process induced by its α-regression quantile, 0 <α< 1. While only the intercept component of the α-regression quantile estimates the quantile F^−1(α) of the model errors, the α also affects the slope components, whose dispersion infinitely increases as α → 0, 1, in the same rate as the variance of the sample α-quantile. The process of the slope components of α-regression quantile over α ∈ (0, 1) is asymptotically nequivalent to the process of R-estimates of the slope parameters in the linear model, generated by the Hájek rank scores. Both processes converge to the vector of independent Brownian bridges under exponentially tailed parent distribution F, after standardization by f (F^−1(α)).

Název v anglickém jazyce

The Process Induced by Slope Components of α-Regression Quantile

Popis výsledku anglicky

We consider the linear regression model, along with the process induced by its α-regression quantile, 0 <α< 1. While only the intercept component of the α-regression quantile estimates the quantile F^−1(α) of the model errors, the α also affects the slope components, whose dispersion infinitely increases as α → 0, 1, in the same rate as the variance of the sample α-quantile. The process of the slope components of α-regression quantile over α ∈ (0, 1) is asymptotically nequivalent to the process of R-estimates of the slope parameters in the linear model, generated by the Hájek rank scores. Both processes converge to the vector of independent Brownian bridges under exponentially tailed parent distribution F, after standardization by f (F^−1(α)).

Druh

C - Kapitola v odborné knize

CEP obor

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OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/GA22-03636S" target="_blank" >GA22-03636S: Agregace metodologií založená na ekonomických datech</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název knihy nebo sborníku

Recent Advances in Econometrics and Statistics

ISBN

978-3-031-61852-9

Počet stran výsledku

10

Strana od-do

231-240

Počet stran knihy

618

Název nakladatele

Springer

Místo vydání

Cham

Kód UT WoS kapitoly

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