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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