Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/79361 
Year of Publication: 
2002
Series/Report no.: 
cemmap working paper No. CWP19/02
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
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 asymptotic distribution of each additive component is the same as it would be if the other components were known with certainty.
Subjects: 
Additive models , multivariate curve estimation , nonparametric regression , kernel estimates , orthogonal series estimator
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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