Nonparametric estimate remarks

Poznámky k neparametrickým odhadům

Jitka Poměnková

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2006, vol. 54, issue 3, 93-100

Abstract: 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.

Keywords: kernel; Gasser-Müller estimator; Nadaraya-Watson estimator; Local linear estimator (search for similar items in EconPapers)
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:mup:actaun:actaun_2006054030093

DOI: 10.11118/actaun200654030093

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