  This paper describes an estimator of the additive components of a
nonparametric additive model with a known link function. When the additive
components are twice continuously differentiable, the estimator is
asymptotically normally distributed with a rate of convergence in probability
of n^{-2/5}. This is true regardless of the (finite) dimension of the
explanatory variable. Thus, in contrast to the existing asymptotically normal
estimator, the new estimator has no curse of dimensionality. Moreover, the
estimator has an oracle property. The asymptotic distribution of each additive
component is the same as it would be if the other components were known with
certainty.
