Sieve empirical likelihood ratio tests for nonparametric functions

@inproceedings{Fan2004SieveEL,
  title={Sieve empirical likelihood ratio tests for nonparametric functions},
  author={Jianqing Fan and Jian Zhang},
  year={2004}
}
Generalized likelihood ratio statistics have been proposed in Fan, Zhang and Zhang (2001) as a generally applicable method for testing nonparametric hypotheses concerning about nonparametric functions. The likelihood ratio statistics are constructed based on the assumption that the distributions of stochastic errors are in a certain parametric family. We extend their work to the case where the error distribution is completely unspecified via newly proposed sieve empirical likelihood ratio tests… CONTINUE READING

From This Paper

Figures, tables, and topics from this paper.

References

Publications referenced by this paper.
Showing 1-10 of 31 references

On the use of nonparametric regression for checking linear relation

A. Azzalini, A. N. Bowman
1993
View 4 Excerpts
Highly Influenced

Empirical likelihood ratio confidence intervals for a single functional,

A. B. Owen
Biometrika • 1988
View 14 Excerpts
Highly Influenced

Test of significance based on wavelet thresholding and Neyman's truncation,

J. Fan
J. Amer. Statist. Assoc., • 1996
View 15 Excerpts
Highly Influenced

Efficient and Adaptive Estimation

P. J. Bickel, C.A.J. Klaassen, Y. Ritov, J. Wellner
ships," J. Roy. Statist. Soc. Ser.B, • 1993
View 3 Excerpts
Highly Influenced

Efficient estimation of models with conditional moment restrictions,

W. K. Newey
Handbook of Statistics, • 1993
View 2 Excerpts
Highly Influenced

Asymptotic comparison of Cramer-von Mises and nonparametric function estimation techniques for testing goodness-of-fit,

R. L. Eubank, V. M. LaRiccia
Ann. Statist., • 1992
View 3 Excerpts
Highly Influenced

Similar Papers

Loading similar papers…