Detail publikace

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

KONEČNÁ, K.

Originální název

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

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Priestley-Chao estimator of conditional density, random design, uniform marginal density, bandwidth selection, maximum likelihood method, reference rule method

Autoři

KONEČNÁ, K.

Vydáno

21. 9. 2018

Nakladatel

Český statistický úřad

Místo

Česká republika

ISSN

0322-788X

Periodikum

Statistika

Ročník

98

Číslo

3

Stát

Česká republika

Strany od

283

Strany do

294

Strany počet

307

URL

Plný text v Digitální knihovně

BibTex

@article{BUT150775,
  author="Kateřina {Pokorová}",
  title="The Priestley-Chao Estimator of Conditional Density with Uniformly Distributed Random Design",
  journal="Statistika",
  year="2018",
  volume="98",
  number="3",
  pages="283--294",
  issn="0322-788X",
  url="https://www.czso.cz/documents/10180/61266313/32019718q3283.pdf/a6025d1a-d8fc-4e3b-9846-3c16c7937288?version=1.0"
}