Data-analytic approaches to regression problems, arising from many
scientific disciplines are described in this book. The aim of these
nonparametric methods is to relax assumptions on the form of a
regression function and to let data search for a suitable function
that describes the data well. The use of these nonparametric
functions with parametric techniques can yield very powerful data
analysis tools. Local polynomial modeling and its applications
provides an up-to-date picture on state-of-the-art nonparametric
regression techniques. The emphasis of the book is on methodologies
rather than on theory, with a particular focus on applications of
nonparametric techniques to various statistical problems.
High-dimensional data-analytic tools are presented, and the book
includes a variety of examples. This will be a valuable reference
for research and applied statisticians, and will serve as a
textbook for graduate students and others interested in
nonparametric regression.
General
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