Preprint #97-20
We explore additive models that combine both parametric and nonparametric
terms and propose a root-n-consistent backfitting estimator for the
parametric component of the model. The theoretical properties of the
estimator
are developed for the case with a single nonparametric term and extended
to an
arbitrary number of nonparametric additive terms. A estimator for the
optimal bandwidth making minimial use of asymptotic expressions for bias
and variance is proposed, and a fast implementation algorithm for
model fitting and bandwidth selection is developed. The practical
behavior of
the estimator and bandwidth selection is illustrated by simulation
experiments.
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Department of Statistics, Snedecor Hall, Ames, IA 50011-1210.