The Priestley-Chao Estimator of Conditional Density with Uniformly Distributed Random Design

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F18%3APU129469" target="_blank" >RIV/00216305:26110/18:PU129469 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.czso.cz/documents/10180/61266313/32019718q3283.pdf/a6025d1a-d8fc-4e3b-9846-3c16c7937288?version=1.0" target="_blank" >https://www.czso.cz/documents/10180/61266313/32019718q3283.pdf/a6025d1a-d8fc-4e3b-9846-3c16c7937288?version=1.0</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

The Priestley-Chao Estimator of Conditional Density with Uniformly Distributed Random Design

Popis výsledku v původním jazyce

The present paper is focused on non-parametric estimation of conditional density. Conditional density can be regarded as a generalization of regression thus the kernel estimator of conditional density can be derived from the kernel estimator of the regression function. We concentrate on the Priestley-Chao estimator of conditional density with a random design presented by a uniformly distributed unconditional variable. The statistical properties of such an estimator are given. As the smoothing parameters have the most significant influence on the quality of the final estimate, the leave-one-out maximum likelihood method is proposed for their detection. Its performance is compared with the cross-validation method and with two alternatives of the reference rule method. The theoretical part is complemented by a simulation study.

Název v anglickém jazyce

The Priestley-Chao Estimator of Conditional Density with Uniformly Distributed Random Design

Popis výsledku anglicky

The present paper is focused on non-parametric estimation of conditional density. Conditional density can be regarded as a generalization of regression thus the kernel estimator of conditional density can be derived from the kernel estimator of the regression function. We concentrate on the Priestley-Chao estimator of conditional density with a random design presented by a uniformly distributed unconditional variable. The statistical properties of such an estimator are given. As the smoothing parameters have the most significant influence on the quality of the final estimate, the leave-one-out maximum likelihood method is proposed for their detection. Its performance is compared with the cross-validation method and with two alternatives of the reference rule method. The theoretical part is complemented by a simulation study.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

10103 - Statistics and probability

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název periodika

Statistika

ISSN

0322-788X

e-ISSN

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Svazek periodika

98

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

307

Strana od-do

283-294

Kód UT WoS článku

000445278600005

EID výsledku v databázi Scopus

2-s2.0-85057962359