Publication details

Additive models and kernel smoothing

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Year of publication 1999
Type Article in Proceedings
Conference PROBASTAT'98 Proceedings of the Third International Conference on Mathematical Statistics
MU Faculty or unit

Faculty of Science

Field General mathematics
Keywords linear smoother; smoother matrices; additive model; orthogonal projection
Description Nonparametric regression methods are often used to estimate an unknown function $m(x_1,\dots,x_p)$ in a regression model $$Y=m(X_1,\dots,X_p)+\eps$$ for random variables $X_1,\dots,X_p,Y$ and error $\eps$. Additive model can be used for the function $m$ in the special form $$m(x_1,\dots,x_p)=m_1(x_1)+\dots m_p(x_p).$$ Application of kernel smoothing to additive models is shown in this contribution and some practical results, too.
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