Free Access
Issue
ESAIM: PS
Volume 12, April 2008
Page(s) 173 - 195
DOI https://doi.org/10.1051/ps:2007047
Published online 23 January 2008
  1. F. Abramovich and Y. Benjamini, Adaptive thresholding of wavelet coefficients. CSDA 4 (1996) 351–361. [Google Scholar]
  2. A. Antoniadis, J. Bigot and T. Sapatinas, Wavelet estimators in nonparametric regression: a comparative simulation study. J. Statist. Software 6 (2001) 1–83. [Google Scholar]
  3. B. Arnold, N. Balakrishnan and H. Nagaraja, A first course in order statistics. Wiley series in probability (1993). [Google Scholar]
  4. A. Barron, L. Birgé and P. Massart, Risk bounds for model selection via penalization. Probab. Theory Related Fields 113 (1999) 301–413. [CrossRef] [MathSciNet] [Google Scholar]
  5. L. Birgé and P. Massart, Minimal penalties for Gaussian model selection. Probab. Theor. Rel. Fields 138 (2007) 33–73. [CrossRef] [MathSciNet] [Google Scholar]
  6. O. Bousquet, Concentration inequalities for sub-additive functions using the entropy method, in Stochastic inequalities and applications, Progr. Probab. Birkhäuser, Basel 56 (2003) 213–247. [Google Scholar]
  7. T. Cai, Adaptive wavelet estimation: a block thresholding and oracle inequality approach. Ann. Stat. 3 (1999) 898–924. [CrossRef] [Google Scholar]
  8. L. de Haan, On regular variation and its application to the weak convergence of sample extremes. 3rd ed., Mathematical Centre Tracts 32 Amsterdam (1975). [Google Scholar]
  9. D. Donoho and J. Jin, Higher criticism for detecting sparse heterogeneous mixtures. Ann. Stat. 32 (2004) 962–994. [CrossRef] [MathSciNet] [Google Scholar]
  10. D. Donoho and I. Johnstone, Ideal spatial adaptation by wavelet shrinkage. Biometrika 81 (1994) 425–455. [CrossRef] [MathSciNet] [Google Scholar]
  11. M. Falk, A note on uniform asymptotic normality of intermidiate order statistics. Ann. Inst. Statist. Math 41 (1989) 19–29. [MathSciNet] [Google Scholar]
  12. J. Fan and R. Li, Variable selection via nonconcave penalized likelihood and its oracle properties. J. Amer. Statist. Assoc. 96 (2001) 1348–1360. [CrossRef] [MathSciNet] [Google Scholar]
  13. T. Hastie, R. Tibshirani and J. Friedman, The elements of statistical learning. Springer, Series in statistics (2001). [Google Scholar]
  14. N. Meinhausen and J. Rice, Estimating the proportion of false null hypothesis among a large number of independently tested hypothesis. Ann. Stat. 34 (2006) 373–393. [CrossRef] [Google Scholar]
  15. M.S. Pinsker, Optimal filtration of square-integrable signals in Gaussian noise. Probl. Peredachi Inform. 2 (1980) 52–68. [Google Scholar]
  16. G. Shorak and J. Wellner, Empirical processes with Applications to Statistics. Wiley (1986). [Google Scholar]
  17. R. Tibshirani, Regression shrinkage and selection via the lasso. J. Roy. Statist. Soc. B 58 (1996) 267–288. [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.