Estimation in additive models with highly or nonhighly correlated covariates

Jiancheng Jiang Yingying Fan Jianqing Fan

Statistics Theory and Methods mathscidoc:1912.43380

The Annals of Statistics, 38, (3), 1403-1432, 2010
Motivated by normalizing DNA microarray data and by predicting the interest rates, we explore nonparametric estimation of additive models with highly correlated covariates. We introduce two novel approaches for estimating the additive components, integration estimation and pooled backfitting estimation. The former is designed for highly correlated covariates, and the latter is useful for nonhighly correlated covariates. Asymptotic normalities of the proposed estimators are established. Simulations are conducted to demonstrate finite sample behaviors of the proposed estimators, and real data examples are given to illustrate the value of the methodology.
No keywords uploaded!
[ Download ] [ 2019-12-21 11:40:45 uploaded by Jianqing_Fan ] [ 599 downloads ] [ 0 comments ]
@inproceedings{jiancheng2010estimation,
  title={Estimation in additive models with highly or nonhighly correlated covariates},
  author={Jiancheng Jiang, Yingying Fan, and Jianqing Fan},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191221114045748004940},
  booktitle={The Annals of Statistics},
  volume={38},
  number={3},
  pages={1403-1432},
  year={2010},
}
Jiancheng Jiang, Yingying Fan, and Jianqing Fan. Estimation in additive models with highly or nonhighly correlated covariates. 2010. Vol. 38. In The Annals of Statistics. pp.1403-1432. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191221114045748004940.
Please log in for comment!
 
 
Contact us: office-iccm@tsinghua.edu.cn | Copyright Reserved