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Direct estimation of low-dimensional components in additive models

Jianqing Fan Wolfgang Hrdle Enno Mammen

Statistics Theory and Methods mathscidoc:1912.43278

The Annals of Statistics, 26, (3), 943-971, 1998
Additive regression models have turned out to be a useful statistical tool in analyses of high-dimensional data sets. Recently, an estimator of additive components has been introduced by Linton and Nielsen which is based on marginal integration. The explicit definition of this estimator makes possible a fast computation and allows an asymptotic distribution theory. In this paper an asymptotic treatment of this estimate is offered for several models. A modification of this procedure is introduced. We consider weighted marginal integration for local linear fits and we show that this estimate has the following advantages.
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@inproceedings{jianqing1998direct,
  title={Direct estimation of low-dimensional components in additive models},
  author={Jianqing Fan, Wolfgang Hrdle, and Enno Mammen},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191221113437020271838},
  booktitle={The Annals of Statistics},
  volume={26},
  number={3},
  pages={943-971},
  year={1998},
}
Jianqing Fan, Wolfgang Hrdle, and Enno Mammen. Direct estimation of low-dimensional components in additive models. 1998. Vol. 26. In The Annals of Statistics. pp.943-971. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191221113437020271838.
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