Free Access
Issue
ESAIM: PS
Volume 15, 2011
Page(s) 180 - 196
DOI https://doi.org/10.1051/ps/2009013
Published online 05 January 2012
  1. J.M. Azaïs and M. Wschebor, Level Sets and Extrema of Random Processes and Fields. Wiley, Hoboken (2009). [Google Scholar]
  2. E.N. Belitser and B.Y. Levit, On minimax filtering over ellipsoids. Math. Methods Statist. 4 (1995) 259–273. [MathSciNet] [Google Scholar]
  3. S.M. Berman, Local times and sample function properties of stationary Gaussian processes. Trans. Amer. Math. Soc. 137 (1969) 277–299. [CrossRef] [MathSciNet] [Google Scholar]
  4. J. Cuzick, Boundary crossing probabilities for stationary Gaussian processes and Brownian motion. Trans. Amer. Math. Soc. 263 (1981) 469–492. [CrossRef] [MathSciNet] [Google Scholar]
  5. D.L. Donoho and I.M. Johnstone, Ideal spatial adaptation by wavelet shrinkage. Biometrika 81 (1994) 425–455. [CrossRef] [MathSciNet] [Google Scholar]
  6. D.L. Donoho and I.M. Johnstone, Adapting to unknown smoothness via wavelet shrinkage. J. Amer. Statist. Assoc. 90 (1995) 1200–1224. [CrossRef] [MathSciNet] [Google Scholar]
  7. D. Geman and J. Horowitz, Occupation densities. Ann. Probab. 8 (1980) 1–67. [CrossRef] [MathSciNet] [Google Scholar]
  8. G.K. Golubev, Minimax filtration of functions in L2. Probl. Inf. Transm. 18 (1982) 272–278. [Google Scholar]
  9. D. Nualart, The Malliavin calculus and related topics. Probability and its Applications. Springer-Verlag, Berlin, second edition (2006). [Google Scholar]
  10. M. Nussbaum, Minimax risk, Pinsker bound, in Encyclopedia of Statistical Sciences, S. Kotz Ed. Wiley, New York (1999). [Google Scholar]
  11. J. Pickands, Upcrossing probabilities for stationary Gaussian processes. Trans. Amer. Math. Soc. 145 (1969) 51–73. [CrossRef] [MathSciNet] [Google Scholar]
  12. M.S. Pinsker, Optimal filtration of square-integrable signals in Gaussian noise. Probl. Inf. Transm. 16 (1980) 52–68. [Google Scholar]
  13. H.V. Poor, An introduction to signal detection and estimation. Springer Texts in Electrical Engineering. Springer-Verlag, New York, second edition (1994). [Google Scholar]
  14. N. Privault and A. Réveillac, Superefficient drift estimation on the Wiener space. C. R. Acad. Sci. Paris Sér. I Math. 343 (2006) 607–612. [CrossRef] [Google Scholar]
  15. N. Privault and A. Réveillac, Stein estimation for the drift of Gaussian processes using the Malliavin calculus. Ann. Stat. 35 (2008) 2531–2550. [CrossRef] [Google Scholar]
  16. N. Privault and A. Réveillac, Stein estimation of Poisson process intensities. Stat. Inference Stoch. Process. 12 (2009) 37–53. [CrossRef] [MathSciNet] [Google Scholar]
  17. C. Qualls and H. Watanabe, Asymptotic properties of Gaussian processes. Ann. Math. Statist. 43 (1972) 580–596. [CrossRef] [MathSciNet] [Google Scholar]
  18. D. Revuz and M. Yor, Continuous martingales and Brownian motion, Vol. 293 of Grundlehren der Mathematischen Wissenschaften. Springer-Verlag, Berlin, third edition (1999). [Google Scholar]
  19. C. Stein, Estimation of the mean of a multivariate normal distribution. Ann. Stat. 9 (1981) 1135–1151. [CrossRef] [MathSciNet] [Google Scholar]
  20. M. Weber, The supremum of Gaussian processes with a constant variance. Prob. Th. Rel. Fields 81 (1989) 585–591. [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.