Free Access
Issue
ESAIM: PS
Volume 7, March 2003
Page(s) 279 - 312
DOI https://doi.org/10.1051/ps:2003013
Published online 15 May 2003
  1. P.J. Bickel and M. Rosenblatt, On Some Global Measures of Deviation of Density Function Estimates. Ann. Statist. 1 (1973) 1071-1095. [CrossRef] [MathSciNet] [Google Scholar]
  2. P. Bickel, C. Klaassen, Y. Ritov and J. Wellner, Efficient and Adaptive Estimation for the Semiparametric Models. John Hopkins University Press, Baltimore (1993). [Google Scholar]
  3. B.M. Brown, Martingale Central Limit Theorems. Ann. Math. Statist. 42 (1971) 59-66. [CrossRef] [MathSciNet] [Google Scholar]
  4. L.D. Brown and M. Low, Asymptotic Equivalence of Nonparametric Regression and White Noise. Ann. Statist. 24 (1996) 2384-2398. [CrossRef] [MathSciNet] [Google Scholar]
  5. M.V. Burnashev, On the Minimax Detection of an Inaccurately Known Signal in a White Gaussian Noise. Theory Probab. Appl. 24 (1979) 107-119. [CrossRef] [Google Scholar]
  6. N.N. Chentsov, Statistical Decision Rules and Optimal Inference. Moskow, Nauka (1972). [Google Scholar]
  7. M.S. Ermakov, Minimax Detection of a Signal in Gaussian White Noise. Theory Probab. Appl. 35 (1990) 667-679. [CrossRef] [MathSciNet] [Google Scholar]
  8. M.S. Ermakov, On Asymptotic Minimaxity of Rank Tests. Statist. Probab. Lett. 15 (1992) 191-196. [CrossRef] [MathSciNet] [Google Scholar]
  9. M.S. Ermakov, Minimax Nonparametric Testing Hypotheses on a Density Function. Theory Probab. Appl. 39 (1994) 396-416. [CrossRef] [MathSciNet] [Google Scholar]
  10. M.S. Ermakov, Asymptotic Minimaxity of Tests of Kolmogorov and Omega-squared Types. Theory Probab. Appl. 40 (1995) 54-67. [MathSciNet] [Google Scholar]
  11. M.S. Ermakov, Asymptotic Minimaxity of Chi-squared Tests. Theory Probab. Appl. 42 (1997) 668-695. [MathSciNet] [Google Scholar]
  12. M.S. Ermakov, On Distinquishability of Two Nonparametric Sets of Hypotheses. Statist. Probab. Lett. 48 (2000) 275-282. [CrossRef] [MathSciNet] [Google Scholar]
  13. Y. Fan, Testing Goodness of Fit of a Parametric Density Function by Kernel Method. Econometric Theory 10 (1994) 316-356. [Google Scholar]
  14. E. Guerre and P. Lavergne, Minimax Rates for Nonparametric Specification Testing in Regression Models, Working Paper. Toulouse University of Social Sciences, Toulouse, France (1999). [Google Scholar]
  15. B.K. Ghosh and Wei-Mion Huang, The Power and Optimal Kernel of the Bickel-Rosenblatt Test for Goodness of Fit. Ann. Statist. 19 (1991) 999-1009. [CrossRef] [MathSciNet] [Google Scholar]
  16. P. Hall, Integrated Square Error Properties of Kernel Estimators of Regression Function. Ann. Statist. 12 (1984) 241-260. [CrossRef] [MathSciNet] [Google Scholar]
  17. P. Hall, Central Limit Theorem for Integrated Square Error of Multivariate Nonparametric Density Estimators. J. Multivar. Anal. 14 (1984) 1-16. [CrossRef] [Google Scholar]
  18. W. Hardle, Applied Nonparametric Regression. Cambridge University Press, Cambridge (1989). [Google Scholar]
  19. J.D. Hart, Nonparametric Smoothing and Lack-of-fit Tests. Springer-Verlag, New York (1997). [Google Scholar]
  20. J.L. Horowitz and V.G. Spokoiny, Adaptive, Rate-optimal Test of Parametric Model against a Nonparametric Alternative, Vol. 542, Preprint. Weierstrass-Institute of Applied Analysis and Stochastic, Berlin (1999). [Google Scholar]
  21. Yu.I. Ingster, Minimax Detection of Signal in lp-metrics. Z. Nauchn. Sem. (POMI) 184 (1990) 152-168. [Google Scholar]
  22. Yu.I. Ingster and I.A. Suslina, Minimax Detection of Signals for Besov Balls and Bodies. Probl. Inform. Transm. 34 (1998) 56-68. [Google Scholar]
  23. Yu.I. Ingster and I.A. Suslina, Nonparametric Goodness-of-Fit Testing under Gaussian Model. Springer-Verlag, New York, Lecture Notes in Statist. 169. [Google Scholar]
  24. V.D. Konakov, On a Global Measure of Deviation for an Estimate of the Regression Line. Theor. Probab. Appl. 22 (1977) 858-868. [CrossRef] [Google Scholar]
  25. O.V. Lepski and V.G. Spokoiny, Minimax Nonparametric Hypothesis Testing: The Case of an Inhomogeneous Alternative. Bernoulli 5 (1999) 333-358. [CrossRef] [MathSciNet] [Google Scholar]
  26. M.A. Lifshits, Gaussian Random Functions. TViMS Kiev (1995). [Google Scholar]
  27. M. Nussbaum, Asymptotic Equivalence of Density Estimation and Gaussian White Noise. Ann. Statist. 24 (1996) 2399-2430. [Google Scholar]
  28. V.I. Piterbarg, Asymptotic Methods in Theory of Gaussian Proceses and Fields. Moskow University, Moskow (1988). [Google Scholar]
  29. J.C.W. Rayner and D.J. Best, Smooth Tests of Goodness of Fit. Oxford University Press, New York (1989). [Google Scholar]
  30. D. Slepian, The One-sided Barrier Problem for Gaussian Noise. Bell System Tech. J. 41 (1962) 463-501. [CrossRef] [MathSciNet] [Google Scholar]
  31. V.G. Spokoiny, Adaptive Hypothesis Testing using Wavelets. Ann. Statist. 24 (1996) 2477-2498. [CrossRef] [MathSciNet] [Google Scholar]
  32. Ch. Stein, Efficient Nonparametric Testing and Estimation, in Third Berkeley Symp. Math. Statist. and Probab, Vol. 1. Univ. California Press, Berkeley (1956) 187-195. [Google Scholar]
  33. W. Stute, Nonparametric Model Checks for Regression. Ann. Statist. 25 (1997) 613-641. [CrossRef] [MathSciNet] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.