Free Access
Issue
ESAIM: PS
Volume 9, June 2005
Page(s) 98 - 115
DOI https://doi.org/10.1051/ps:2005004
Published online 15 November 2005
  1. J. Aaronson, R. Burton, H. Dehling, D. Gilat, T. Hill and B. Weiss, Strong laws for L- and U-statistics. Trans. Amer. Math. Soc. 348 (1996) 2845–2866. [CrossRef] [MathSciNet] [Google Scholar]
  2. P. Billingsley, Convergence of probability measures. Wiley Series in Probability and Statistics: Probability and Statistics. John Wiley & Sons Inc., New York, second edition. A Wiley-Interscience Publication (1999). [Google Scholar]
  3. E. Bolthausen, A central limit theorem for two-dimensional random walks in random sceneries. Ann. Probab. 17 (1989) 108–115. [CrossRef] [MathSciNet] [Google Scholar]
  4. E. Boylan, Local times for a class of Markoff processes. Illinois J. Math. 8 (1964) 19–39. [MathSciNet] [Google Scholar]
  5. E. Buffet and J.V. Pulé, A model of continuous polymers with random charges. J. Math. Phys. 38 (1997) 5143–5152. [CrossRef] [MathSciNet] [Google Scholar]
  6. P. Cabus and N. Guillotin-Plantard, Functional limit theorems for U-statistics indexed by a random walk. Stochastic Process. Appl. 101 (2002) 143–160. [CrossRef] [MathSciNet] [Google Scholar]
  7. F. den Hollander, Mixing properties for random walk in random scenery. Ann. Probab. 16 (1988) 1788–1802. [CrossRef] [MathSciNet] [Google Scholar]
  8. F. den Hollander, M.S. Keane, J. Serafin and J.E. Steif, Weak bernoullicity of random walk in random scenery. Japan. J. Math. (N.S.) 29 (2003) 389–406. [MathSciNet] [Google Scholar]
  9. F. den Hollander and J.E. Steif, Mixing properties of the generalized T,T-1-process. J. Anal. Math. 72 (1997) 165–202. [CrossRef] [MathSciNet] [Google Scholar]
  10. R.K. Getoor and H. Kesten, Continuity of local times for Markov processes. Comp. Math. 24 (1972) 277–303. [Google Scholar]
  11. W. Hoeffding, The strong law of large numbers for U-statistics. Univ. N. Carolina, Institue of Stat. Mimeo series 302 (1961). [Google Scholar]
  12. H. Kesten and F. Spitzer, A limit theorem related to a new class of self-similar processes. Z. Wahrsch. Verw. Gebiete 50 (1979) 5–25. [CrossRef] [MathSciNet] [Google Scholar]
  13. A.J. Lee, U-statistics. Theory and practice. Marcel Dekker, Inc., New York (1990). [Google Scholar]
  14. M. Maejima, Limit theorems related to a class of operator-self-similar processes. Nagoya Math. J. 142 (1996) 161–181. [MathSciNet] [Google Scholar]
  15. S. Martínez and D. Petritis, Thermodynamics of a Brownian bridge polymer model in a random environment. J. Phys. A 29 (1996) 1267–1279. [CrossRef] [MathSciNet] [Google Scholar]
  16. I. Meilijson, Mixing properties of a class of skew-products. Israel J. Math. 19 (1974) 266–270. [CrossRef] [MathSciNet] [Google Scholar]
  17. D. Revuz and M. Yor, Continuous martingales and Brownian motion. Springer-Verlag, Berlin. Fundamental Principles of Mathematical Sciences 293 (1999). [Google Scholar]
  18. R.J. Serfling, Approximation theorems of mathematical statistics. John Wiley & Sons Inc., New York. Wiley Series in Probability and Mathematical Statistics (1980). [Google Scholar]
  19. F. Spitzer, Principles of random walks. Springer-Verlag, New York, second edition. Graduate Texts in Mathematics 34 (1976). [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.