Testing for superiority among two regression curves

Journal of Statistical Planning and Inference

Volumn 117, Issue 1, 2003, Pages 15-33

  Koul, Hira L ^a   Schick, Anton ^b  

^a MICHIGAN STATE UNIVERSITY   (United States)

^b BINGHAMTON UNIVERSITY   (United States)

Author keywords

Covariate matching; Locally asymptotically most powerful

Indexed keywords

EID: 0042012784     PISSN: 03783758     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0378-3758(02)00364-6     Document Type: Article

References (23)

1. Bickel P.J. Klaassen C.A.J. Ritov Y. Wellner J.A. Efficient and Adaptive Estimation for Semiparametric Models 1993 Johns Hopkins University Press Baltimore
2. Cabus, P., 1999. Testing for the comparison of non-parametric regression curves. University of Rennes, preprint.
3. Choi S. Hall W.J. Schick A. Asymptotically uniformly most powerful tests in parametric and semiparametric models Ann. Statist. 24 1996 841-861
4. Cox D. Koh E. Wahba G. Yandell B.S. Testing the (parametric) null model hypothesis in (semiparametric) partial and generalized spline models Ann. Statist. 16 1988 113-119
5. Delgado M.A. Testing the equality of nonparametric regression curves Statist. Probab. Lett. 17 1993 199-204
6. Eubank R.L. Spiegelman C.H. Testing the goodness-of-fit of a linear model via nonparametric regression techniques J. Amer. Statist. Assoc. 85 1990 387-392
7. Hájek J. vSidák Z. Theory of Rank Tests 1967 Academic Press New York
8. Hall P. Hart J.D. Bootstrap test for difference between means in nonparametric regression J. Amer. Statist. Assoc. 85 1990 1039-1049
9. Hall, P., Turlach, B.A., 1995. Enhancing convolution and interpolation methods for nonparametric regression. CMA, Canberra, unpublished manuscript.
10. Hall P. Huber C. Speckman P.L. Covariate-matched one-sided tests for the difference between functional means J. Amer. Statist. Assoc. 92 1997 1074-1083
11. Härdle W. Mammen E. Comparing nonparametric versus parametric regression fits Ann. Statist. 21 1993 1926-1947
12. Härdle W. Marron J.S. Semiparametric comparisons of regression curves Ann. Statist. 18 1990 63-89
13. King E. Hart J.D. Wehrly T.E. Testing the equality of two regression curves using linear smoothers Statist. Probab. Lett. 12 1991 239-247
14. Koul H.L. Schick A. Testing for the equality of two nonparametric regression curves J. Statist. Plann. Inference 65 1997 293-314
15. Raz J. Testing for no effect when estimating a smooth function by nonparametric regression: a randomization approach J. Amer. Statist. Assoc. 85 1990 132-138
16. Rudin W. Real and Complex Analysis 2nd Edition 1974 McGraw-Hill New York
17. Scheike T.H. Comparison of non-parametric regression functions through their cumulatives Statist. Probab. Lett. 46 2000 21-32
18. Schick A. A note on the construction of asymptotically linear estimators J. Statist. Plann. Inference 16 1987 89-105 Correction (1989), 22, 269-270
19. Schick A. On efficient estimation in regression models Ann. Statist. 21 1993 1486-1521 Correction and Addendum, 23 (1995) 1862-1863.
20. Schick A. Efficient estimation in regression models with unknown scale functions Math. Methods Statist. 3 1994 171-212
21. Schick A. Efficient estimates in linear and nonlinear regression with heteroscedastic errors J. Statist. Plann. Inference 58 1997 371-387
22. Serfling, R.J., 1980. Approximation theorems of mathematical statistics. Wiley Series in Probability and Mathematical Statistics. John Wiley & Sons, Inc., New York.
23. Stute W. Nonparametric model checks for regression Ann. Statist. 26 1997 613-641