Arbeitspapier

Nonparametric estimation of an additive model with a link function

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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.

Language
Englisch

Bibliographic citation
Series: SFB 373 Discussion Paper ; No. 2002,63

Classification
Wirtschaft
Subject
nonparametric regression
additive models
multivariate curve estimation
kernel estimates
orthogonal series estimator

Event
Geistige Schöpfung
(who)
Horowitz, Joel L.
Mammen, Enno
Event
Veröffentlichung
(who)
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes
(where)
Berlin
(when)
2002

Handle
URN
urn:nbn:de:kobv:11-10049252
Last update
10.03.2025, 11:42 AM CET

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Object type

  • Arbeitspapier

Associated

  • Horowitz, Joel L.
  • Mammen, Enno
  • Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

Time of origin

  • 2002

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