(1996). Comments on 'A personal view of smoothing and statistics' by J.S. Marron, 'Smoothing by local regression: principles and methods' by W.S. Cleveland and C. Loader, and 'Variance properties of local polynomials and ensuing modifications' by B Seifert and T. Gasser.
In: Hardle, W and Schimek, M.G. eds.
Statistical Theory and Computational Aspects of Smoothing.
Heidelberg: Physica-Verlag, pp. 85–87.
About the book:
One of the main applications of statistical smoothing techniques is nonparametric regression. For the last 15 years there has been a strong theoretical interest in the development of such techniques. Related algorithmic concepts have been a main concern in computational statistics. Smoothing techniques in regression as well as other statistical methods are increasingly applied in biosciences and economics. But they are also relevant for medical and psychological research. Introduced are new developments in scatterplot smoothing and applications in statistical modelling. The treatment of the topics is on an intermediate level avoiding too much technicalities. Computational and applied aspects are considered throughout. Of particular interest to readers is the discussion of recent local fitting techniques.
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