Priestley-Chao Estimator of Conditional Density

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F17%3A00095286" target="_blank" >RIV/00216224:14310/17:00095286 - isvavai.cz</a>
Alternative codes found
RIV/00216305:26110/17:PU125904
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Priestley-Chao Estimator of Conditional Density
Original language description
This contribution is focused on a non-parametric estimation of conditional density. Several types of kernel estimators of conditional density are known, the Nadaraya-Watson and the local linear estimators are the widest used ones. We focus on a new estimator - the Priestley-Chao estimator of conditional density. As conditional density can be regarded as a generalization of regression, the Priestley-Chao estimator, proposed initially for kernel regression, is extended for kernel estimation of conditional density. The conditional characteristics and the statistical properties of the suggested estimator are derived. The estimator depends on the smoothing parameters called bandwidths which influence the final quality of the estimate significantly. The cross-validation method is suggested for their estimation and the expression for the cross-validation function is derived.
Czech name
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Czech description
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Project
<a href="/en/project/GA15-06991S" target="_blank" >GA15-06991S: Functional data analysis and related topics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Mathematics, Information Technologies and Applied Sciences 2017, post-conference proceedings of extended versions of selected papers
ISBN
9788075820266
ISSN
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e-ISSN
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Number of pages
13
Pages from-to
151-163
Publisher name
University of Defence, Brno, 2017
Place of publication
Brno
Event location
Brno
Event date
Jun 15, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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