Free Access
Issue
ESAIM: PS
Volume 11, February 2007
Special Issue: "Stochastic analysis and mathematical finance" in honor of Nicole El Karoui's 60th birthday
Page(s) 102 - 114
DOI https://doi.org/10.1051/ps:2007009
Published online 31 March 2007
  1. K. Azuma, Weighted sums of certain dependent random variables. Tôkohu Math. J. 19 (1967) 357–367. [CrossRef] [Google Scholar]
  2. H.C.P. Berbee, Random walks with stationary increments and renewal theory. Mathematical Centre Tracts 112, Mathematisch Centrum, Amsterdam (1979). [Google Scholar]
  3. L. Birgé and P. Massart, An adaptive compression algorithm in Besov Spaces. Constr. Approx. 16 (2000) 1–36. [CrossRef] [MathSciNet] [Google Scholar]
  4. P. Collet, S. Martinez and B. Schmitt, Exponential inequalities for dynamical measures of expanding maps of the interval. Probab. Theory Relat. Fields 123 (2002) 301–322. [CrossRef] [Google Scholar]
  5. J. Dedecker and F. Merlevède, The conditional central limit theorem in Hilbert spaces. Stoch. Processes Appl. 108 (2003) 229–262. [Google Scholar]
  6. J. Dedecker and C. Prieur, Coupling for Formula -dependent sequences and applications. J. Theoret. Probab. 17 (2004) 861–885. [CrossRef] [MathSciNet] [Google Scholar]
  7. J. Dedecker and C. Prieur, New dependence coefficients. Examples and applications to statistics. Probab. Theory Relat. Fields 132 (2005) 203–236. [CrossRef] [Google Scholar]
  8. J. Dedecker and E. Rio, On the functional central limit theorem for stationary processes. Ann. Inst. H. Poincaré Probab. Statist. 36 (2000) 1–34. [CrossRef] [MathSciNet] [Google Scholar]
  9. P. Doukhan, P. Massart and E. Rio, Invariance principle for absolutely regular empirical processes. Ann. Inst. H. Poincaré Probab. Statist. 31 (1995) 393–427. [MathSciNet] [Google Scholar]
  10. M.I. Gordin, The central limit theorem for stationary processes. Dokl. Akad. Nauk SSSR 188 (1969) 739–741. [MathSciNet] [Google Scholar]
  11. P. Massart, The tight constant in the Dvoretzky-Kiefer-Wolfowitz inequality. Ann. Probab. 18 (1990) 1269–1283. [CrossRef] [MathSciNet] [Google Scholar]
  12. F. Merlevède and M. Peligrad, On the coupling of dependent random variables and applications, in Empirical process techniques for dependent data, Birkhäuser (2002) 171–193. [Google Scholar]
  13. P. Oliveira and C. Suquet, Formula weak convergence of the empirical process for dependent variables, in Wavelets and statistics (Villard de Lans 1994), Lect. Notes Statist. 103 (1995) 331–344. [Google Scholar]
  14. P. Oliveira and C. Suquet, Weak convergence in Formula of the uniform empirical process under dependence. Statist. Probab. Lett. 39 (1998) 363–370. [CrossRef] [MathSciNet] [Google Scholar]
  15. I.F. Pinelis, An approach to inequalities for the distributions of infinite-dimensional martingales, in Probability in Banach spaces, Proc. Eight Internat. Conf. 8 (1992) 128–134. [Google Scholar]
  16. E. Rio, Inégalités de Hoeffding pour les fonctions lipschitziennes de suites dépendantes. C. R. Acad. Sci. Paris Série I 330 (2000) 905–908. [Google Scholar]
  17. A.W. van der Vaart, Bracketing smooth functions. Stoch. Processes Appl. 52 (1994) 93–105. [CrossRef] [Google Scholar]
  18. W.A. Woyczyński, A central limit theorem for martingales in Banach spaces. Bull. Acad. Polon. Sci. Sr. Sci. Math. Astronom. Phys. 23 (1975) 917–920. [Google Scholar]
  19. V.V. Yurinskii, Exponential bounds for large deviations. Theory Prob. Appl. 19 (1974) 154–155. [CrossRef] [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.