Nonparametric Kernel Regression and Its Real Data Application

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F17%3A43933044" target="_blank" >RIV/49777513:23520/17:43933044 - isvavai.cz</a>
Result on the web
<a href="http://fim2.uhk.cz/mme/conferenceproceedings/mme2017_conference_proceedings.pdf" target="_blank" >http://fim2.uhk.cz/mme/conferenceproceedings/mme2017_conference_proceedings.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Nonparametric Kernel Regression and Its Real Data Application
Original language description
This paper deals with the problem of nonparametric kernel estimation, particularly nonparametric kernel estimation of the regression functions. This nonparametric approach is useful in the case, when we need to find some relation between a pair of random variables for further analysis. There are many fields of application in macroeconomics and therefore this paper is focused on estimates of the regression functions on some selected real data sets (number of deaths, marriages and births etc.) First, there is described nonparametric kernel estimation of the regression function with using Nadaraya–Watson approach and influences of the main parameters (smoothing parameter, kernel function etc.) on the properties of the regression function. Then, there is analyzed smoothing pa-rameter and its estimation by different approaches (Penalty methods, RSS method, Cross-validation method and other proposed methods). The obtained results are applied and discussed on selected real data sets.
Czech name
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Czech description
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Project
<a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</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
35th International Conference Mathematical Methods in Economics, MME2017, Conference Proceedings
ISBN
978-80-7435-678-0
ISSN
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e-ISSN
neuvedeno
Number of pages
6
Pages from-to
813-818
Publisher name
Faculty of Informatics and Management, University of Hradec Králové
Place of publication
Hradec Králové
Event location
Hradec Králové, Czech Republic
Event date
Sep 13, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000427151400139

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