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Confidence intervals for nonparametric regression functions under negatively associated errors

Author

Listed:
  • Yongsong Qin
  • Yinghua Li
  • Weizhen Yang
  • Qingzhu Lei

Abstract

In this paper, we study the construction of confidence intervals for a nonparametric regression function under a negatively associated sample by using the blockwise technique. It is shown that the blockwise empirical likelihood (EL) ratio statistic is asymptotically χ2 distributed. The result is used to obtain EL-based confidence intervals for a nonparametric regression function. The results of a simulation study on the finite sample performance of the proposed confidence intervals are reported.

Suggested Citation

  • Yongsong Qin & Yinghua Li & Weizhen Yang & Qingzhu Lei, 2011. "Confidence intervals for nonparametric regression functions under negatively associated errors," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(3), pages 645-659.
    • Handle: RePEc:taf:gnstxx:v:23:y:2011:i:3:p:645-659
    DOI: 10.1080/10485252.2011.566335
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    References listed on IDEAS

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    1. Li, Bo & Liu, Luqin, 2004. "The characterization of equilibrium potentials and last exit distributions for elliptic diffusion processes," Statistics & Probability Letters, Elsevier, vol. 70(2), pages 155-169, November.
    2. Liang, Han-Ying & Su, Chun, 1999. "Complete convergence for weighted sums of NA sequences," Statistics & Probability Letters, Elsevier, vol. 45(1), pages 85-95, October.
    3. Zhang, Li-Xin, 2001. "The Weak Convergence for Functions of Negatively Associated Random Variables," Journal of Multivariate Analysis, Elsevier, vol. 78(2), pages 272-298, August.
    4. Huang, Wen-Tao & Xu, Bing, 2002. "Some maximal inequalities and complete convergences of negatively associated random sequences," Statistics & Probability Letters, Elsevier, vol. 57(2), pages 183-191, April.
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