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: cemmap working paper ; No. CWP19/02

Classification
Wirtschaft
Subject
Additive models , multivariate curve estimation , nonparametric regression , kernel estimates , orthogonal series estimator
Nichtparametrisches Verfahren
Schätztheorie
Theorie

Event
Geistige Schöpfung
(who)
Horowitz, Joel
Mammen, Enno
Event
Veröffentlichung
(who)
Centre for Microdata Methods and Practice (cemmap)
(where)
London
(when)
2002

DOI
doi:10.1920/wp.cem.2002.1902
Handle
Last update
10.03.2023, 11:51 AM CET

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Object type

  • Arbeitspapier

Associated

  • Horowitz, Joel
  • Mammen, Enno
  • Centre for Microdata Methods and Practice (cemmap)

Time of origin

  • 2002

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