RT Journal Article
SR Electronic
A1 Poměnková, Jitka
T1 Nonparametric estimate remarks
JF Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis
YR 2014
VO 54
IS 3
SP 93
OP 100
DO 10.11118/actaun200654030093
UL https://acta.mendelu.cz/artkey/acu-200603-0009.php
AB Kernel smoothers belong to the most popular nonparametric functional estimates. They provide a simple way of finding structure in data. The idea of the kernel smoothing can be applied to a simple fixed design regression model. This article is focused on kernel smoothing for fixed design regresion model with three types of estimators, the Gasser-Müller estimator, the Nadaraya-Watson estimator and the local linear estimator. At the end of this article figures for ilustration of desribed estimators on simulated and real data sets are shown.