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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
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Vydáno
21. 9. 2018
Nakladatel
Český statistický úřad
Místo
Česká republika
ISSN
0322-788X
Periodikum
Statistika
Ročník
98
Číslo
3
Stát
Strany od
283
Strany do
294
Strany počet
307
URL
https://www.czso.cz/documents/10180/61266313/32019718q3283.pdf/a6025d1a-d8fc-4e3b-9846-3c16c7937288?version=1.0
Plný text v Digitální knihovně
http://hdl.handle.net/11012/178454
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" }