Detail publikace

The leave-one-out maximum likelihood method for the priestley-chao estimator of conditional density

KONEČNÁ, K.

Originální název

The leave-one-out maximum likelihood method for the priestley-chao estimator of conditional density

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The contribution is focused on a kernel estimation of conditional density. Kernel smoothing is still popular non-parametric method, in theory as well as in practice. The Priestley-Chao estimator of conditional density is introduced and the statistical properties of the estimator are given. The smoothing parameters called bandwidths play a significant role in kernel smoothing. This is the reason for suggesting the methods for their estimation. The typical approach - the cross-validation method - is supplemented with the leave-one-out maximum log-likelihood method. The performance of the suggested methods is compared via a simulation study and an application on a real data set.

Klíčová slova

kernel smoothing; conditional density; bandwidths; Priestlez-Chao estimator; leave-one-out maximum likelihood method; cross-validation method

Autoři

KONEČNÁ, K.

Vydáno

6. 2. 2018

Nakladatel

Slovak University of Technology in Bratislava in publishing house SPEKTRUM STU

Místo

Bratislava

ISBN

978-80-227-4765-3

Kniha

Proceedings, 17th Conference on Applied Mathematics – APLIMAT 2018

Edice

First edition

Strany od

577

Strany do

589

Strany počet

13

URL

http://evlm.stuba.sk/APLIMAT2018/proceedings/

BibTex

@inproceedings{BUT145510,
  author="Kateřina {Pokorová}",
  title="The leave-one-out maximum likelihood method for the priestley-chao estimator of conditional density",
  booktitle="Proceedings, 17th Conference on Applied Mathematics – APLIMAT 2018",
  year="2018",
  series="First edition",
  pages="577--589",
  publisher="Slovak University of Technology in Bratislava in publishing house SPEKTRUM STU",
  address="Bratislava",
  isbn="978-80-227-4765-3",
  url="http://evlm.stuba.sk/APLIMAT2018/proceedings/"
}