Detailed Information on Publication Record
2016
Selection of bandwidth for kernel regression
KOLÁČEK, Jan and Ivanka HOROVÁBasic information
Original name
Selection of bandwidth for kernel regression
Name in Czech
Hledání optimální šířky okna při jádrové regresi
Authors
KOLÁČEK, Jan (203 Czech Republic, guarantor, belonging to the institution) and Ivanka HOROVÁ (203 Czech Republic, belonging to the institution)
Edition
Communications in Statistics - Theory and Methods, Marcel Dekker, 2016, 0361-0926
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
10101 Pure mathematics
Country of publisher
United States of America
Confidentiality degree
není předmětem státního či obchodního tajemství
Impact factor
Impact factor: 0.311
RIV identification code
RIV/00216224:14310/16:00087701
Organization unit
Faculty of Science
UT WoS
000371090100020
Keywords in English
kernel regression; bandwidth selection; iterative method
Tags
International impact, Reviewed
Změněno: 13/3/2018 17:19, doc. Mgr. Jan Koláček, Ph.D.
Abstract
V originále
The most important factor in kernel regression is a choice of a bandwidth. Considerable attention has been paid to extension the idea of an iterative method known for a kernel density estimate to kernel regression. Data-driven selectors of the bandwidth for kernel regression are considered. The proposed method is based on an optimally balanced relation between the integrated variance and the integrated square bias. This approach leads to an iterative quadratically convergent process. The analysis of statistical properties shows the rationale of the proposed method. In order to see statistical properties of this method the consistency is determined. The utility of the method is illustrated through a simulation study and real data applications.
Links
| GA15-06991S, research and development project |
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