Local polynomial estimation of regression functions for mixing processes

Elias Masry Jianqing Fan

Statistics Theory and Methods mathscidoc:1912.43281

Scandinavian Journal of Statistics, 24, (2), 165-179, 1997.6
Local polynomial fitting has many exciting statistical properties which where established under i.i.d. setting. However, the need for nonlinea r time series modeling, constructing predictive intervals, understanding divergence of nonlinear time series requires the development of the theory of local polynomial fitting for dependent data. In this paper, we study the problem of estimating conditional mean functions and their derivatives via a local polynomial fit. The functions include conditional moments, conditional distribution as well as conditional density functions. Joint asymptotic normality for derivative estimation is established for both strongly mixing and mixing processes.
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@inproceedings{elias1997local,
  title={Local polynomial estimation of regression functions for mixing processes},
  author={Elias Masry, and Jianqing Fan},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191221113446657816841},
  booktitle={Scandinavian Journal of Statistics},
  volume={24},
  number={2},
  pages={165-179},
  year={1997},
}
Elias Masry, and Jianqing Fan. Local polynomial estimation of regression functions for mixing processes. 1997. Vol. 24. In Scandinavian Journal of Statistics. pp.165-179. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191221113446657816841.
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