Detailed Information on Publication Record
2002
Kernel Estimation of the Regression Function - Bandwidth Selection
KOLÁČEK, JanBasic information
Original name
Kernel Estimation of the Regression Function - Bandwidth Selection
Name in Czech
Jádrové odhady regresní funkce - volba optimální šířky okna
Authors
KOLÁČEK, Jan (203 Czech Republic, guarantor, belonging to the institution)
Edition
Brno, Datastat 01, Folia Fac. Sci. Nat. Univ. Masaryk. Brunensis, Mathematica 11, p. 129-138, 10 pp. 2002
Publisher
Masaryk University
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10103 Statistics and probability
Country of publisher
Czech Republic
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
printed version "print"
RIV identification code
RIV/00216224:14310/02:00021250
Organization unit
Faculty of Science
ISBN
80-210-3028-3
Keywords in English
Regression function; kernel smoothing; bandwidth
Tags
Reviewed
Změněno: 12/11/2013 16:18, doc. Mgr. Jan Koláček, Ph.D.
V originále
The problem of deciding how much to smooth is of great importance in nonparametric regression. Before embarking on technical solutions of the problem it is worth noting that a selection of the smoothing parameter is always related to a certain interpretation of the smooth. However, a good automatically selected parameter is always a useful starting (view)point. An advantage of automatic selection of the bandwidth for kernel smoothers is that comparison between laboratories can be made on the basis of a standardized method. Various methods for choosing the smoothing parameter are presented in the following sections. The choice is made so that some global error criterion is minimized. This paper shortly aspires to summarize attained results from this branch and to demonstrate their application for simulated data sets.
In Czech
Práce se zabývá některými metodami pro výběr optimální šířky okna při neparametrické regresi.
Links
| MSM 143100001, plan (intention) |
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