Free Access
Issue
ESAIM: PS
Volume 12, April 2008
Page(s) 273 - 307
DOI https://doi.org/10.1051/ps:2007039
Published online 08 May 2008
  1. J.A. Adell and P. Jodrá, The median of the Poisson distribution. Metrika 61 3 (2005) 337–346. [CrossRef] [Google Scholar]
  2. P. Baufays and J.-P. Rasson, A new geometric discriminant rule. Comput. Stat. Q. 2 (1985) 15–30. [Google Scholar]
  3. P. Billingsley, Convergence of Probability measures. Wiley (1968). [Google Scholar]
  4. D. Deprins, L. Simar and H. Tulkens, Measuring Labor Efficiency in Post Offices, in The Performance of Public Enterprises: Concepts and Measurements, M. Marchand, P. Pestieau and H. Tulkens Eds., North Holland, Amsterdam (1984). [Google Scholar]
  5. J.D. Deuschel and D.W. Stroock, Large Deviations. Pure and Applied Mathematics, 137. Boston, MA Academic Press (1989). [Google Scholar]
  6. L.P. Devroye and G.L. Wise, Detection of abnormal behavior via non parametric estimation of the support. SIAM J. Appl. Math. 38 (1980) 448–480. [Google Scholar]
  7. A. Dembo and O. Zeitouni, Large Deviations Techniques and Applications. Jones and Bartlett, Boston and London (1993). [Google Scholar]
  8. L. Gardes, Estimating the support of a Poisson process via the Faber-Schauder basis and extrems values. Publications de l'Institut de Statistique de l'Université de Paris XLVI 43–72 (2002). [Google Scholar]
  9. J. Geffroy, Sur un problème d'estimation géométrique. Publications de l'Institut de Statistique de l'Université de Paris XIII (1964) 191–200. [Google Scholar]
  10. I. Gijbels, E. Mammen, B.U. Park and L. Simar, On estimation of monotone and concave frontier functions. J. Amer. Statist. Assoc. 94 (1999) 220–228. [CrossRef] [MathSciNet] [Google Scholar]
  11. S. Girard and P. Jacob, Projection estimates of point processes boundaries. J. Statist. Planning Inference 116 (2003), 1–15. [Google Scholar]
  12. S. Girard and P. Jacob, Extreme values and kernel estimates of point processes boundaries. ESAIM: PS 8 (2005) 150–168 . [CrossRef] [EDP Sciences] [Google Scholar]
  13. S. Girard and L. Menneteau, Central limit theorems for smoothed extreme value estimates of Poisson point processes boundaries. J. Statist. Planning Inference 135 (2005) 433–460. [CrossRef] [Google Scholar]
  14. S. Girard and L. Menneteau, Smoothed extreme value estimators of non uniform boundaries with applications to star-shaped supports estimation. Submitted. [Google Scholar]
  15. A. Hardy and J.P. Rasson, Une nouvelle approche des problèmes de classification automatique. Statist. Anal. Données 7 (1982) 41–56. [Google Scholar]
  16. P. Hall, M. Nussbaum and S.E. Stern, On the estimation of a support curve of indeterminate sharpness. J. Multivariate Anal. 62 (1997) 204–232. [CrossRef] [MathSciNet] [Google Scholar]
  17. P. Hall, B.U. Park and S.E. Stern, On polynomial estimators of frontiers and boundaries. J. Multivariate Anal. 66 (1998) 71–98. [CrossRef] [MathSciNet] [Google Scholar]
  18. W. Härdle, Applied nonparametric regression. Cambridge University Press, Cambridge (1990). [Google Scholar]
  19. W. Härdle, P. Hall and L. Simar, Iterated bootstrap with application to frontier models. J. Productivity Anal. 6 (1995) 63–76. [CrossRef] [Google Scholar]
  20. W. Härdle, B.U. Park and A.B. Tsybakov, Estimation of a non sharp support boundaries. J. Multivariate Anal. 43 (1995) 205–218. [Google Scholar]
  21. J.A. Hartigan, Clustering Algorithms. Wiley, Chichester (1975). [Google Scholar]
  22. W. Kallenberg, Intermediate efficiency theory and examples. Ann. Statist. 11 (1983) 170–182. [CrossRef] [MathSciNet] [Google Scholar]
  23. W. Kallenberg, On moderate deviation theory in estimation. Ann. Statist. 11 (1983) 498–504. [CrossRef] [MathSciNet] [Google Scholar]
  24. A.P. Korostelev, L. Simar and A.B. Tsybakov, Efficient estimation of monotone boundaries. Ann. Statist. 23 (1995) 476–489. [CrossRef] [MathSciNet] [Google Scholar]
  25. A.P. Korostelev and A.B. Tsybakov, Minimax theory of image reconstruction, in Lecture Notes in Statistics 82, Springer-Verlag, New York (1993). [Google Scholar]
  26. A.P. Korostelev and A.B. Tsybakov, Asymptotic efficiency of the estimation of a convex set. Problems Inform. Transmission 30 (1994) 317–327. [MathSciNet] [Google Scholar]
  27. E. Mammen and A.B. Tsybakov, Asymptotical minimax recovery of sets with smooth boundaries. Ann. Statist. 23 (1995) 502–524. [CrossRef] [MathSciNet] [Google Scholar]
  28. L. Menneteau, Limit theorems for piecewise constant kernel smoothed estimates of point process boundaries. Technical Report (2007). [Google Scholar]
  29. A. Mokkadem and M. Pelletier, Moderate deviations for the kernel mode estimator and some applications. J. Statist. Planning Inference 135 (2005) 276–299. [CrossRef] [Google Scholar]
  30. V.V. Petrov, Limit theorems of probability theory. Sequences of independent random variables. Oxford Studies in Probability, (1995) 4. [Google Scholar]
  31. G.R. Shorack and J.A. Wellner, Empirical processes with applications to statistics. Wiley, New York (1986). [Google Scholar]
  32. G.P. Tolstov, Fourier series. 2nd ed. New York: Dover Publications (1976). [Google Scholar]
  33. A.B. Tsybakov, On nonparametric estimation of density level sets. Ann. Statist. 25 (1997) 948–969. [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.