Nonparametric estimate remarks
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 mo...
| الحاوية / القاعدة: | Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis |
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| المؤلف الرئيسي: | |
| التنسيق: | مقال |
| اللغة: | الإنجليزية |
| منشور في: |
Mendel University Press
2006-01-01
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://acta.mendelu.cz/54/3/0093/ |
| الملخص: | 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. |
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| تدمد: | 1211-8516 2464-8310 |