This book presents a unified approach on nonparametric estimators
for models of independent observations, jump processes and
continuous processes. New estimators are defined and their limiting
behavior is studied. From a practical point of view, the book
expounds on the construction of estimators for functionals of
processes and densities, and provides asymptotic expansions and
optimality properties from smooth estimators. It also presents new
regular estimators for functionals of processes, compares histogram
and kernel estimators, compares several new estimators for
single-index models, and it examines the weak convergence of the
estimators.
General
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