  Motivated by normalizing DNA microarray data and by predicting the interest
rates, we explore nonparametric estimation of additive models with highly
correlated covariates. We introduce two novel approaches for estimating the
additive components, integration estimation and pooled backfitting estimation.
The former is designed for highly correlated covariates, and the latter is
useful for nonhighly correlated covariates. Asymptotic normalities of the
proposed estimators are established. Simulations are conducted to demonstrate
finite sample behaviors of the proposed estimators, and real data examples are
given to illustrate the value of the methodology.
