Free Access
Issue
ESAIM: PS
Volume 17, 2013
Page(s) 1 - 12
DOI https://doi.org/10.1051/ps/2011112
Published online 06 December 2012
  1. R.R. Bahadur, Some limit theorems in statistics. CBMS-NSF Regional Conference Series in Appl. Math. SIAM, Society for Industrial and Applied Mathematics, Philadelphia, Pa. (1971). [Google Scholar]
  2. H. Chernoff, A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations. Ann. Math. Statist. 23 (1952) 493–507. [CrossRef] [MathSciNet] [Google Scholar]
  3. E. Cuvelier and M. Noirhomme-Fraiture, An approach to stochastic process using quasi-arithmetic means, in Recent advances in stochastic modeling and data analysis, World Scientific (2007) 2–9. [Google Scholar]
  4. E. Cuvelier and M. Noirhomme-Fraiture, Parametric families of probability distributions for functional data using quasi-arithmetic means with Archimedean generators, in Functional and operatorial statistics, Contrib. Statist. Springer (2008) 127–133. [Google Scholar]
  5. V.H. de la Peña, T.L. Lai and Q.-M. Shao, Self-normalized processes : Limit theory and statistical applications, in Probab. Appl. (New York). Springer-Verlag, Berlin (2009). [Google Scholar]
  6. A. Dembo and Q.-M. Shao, Self-normalized large deviations in vector spaces, in High dimensional probability (Oberwolfach, 1996), Birkhäuser, Basel. Progr. Probab. 43 (1998) 27–32. [Google Scholar]
  7. A. Dembo and Q.-M. Shao, Large and moderate deviations for Hotelling’s T2-statistic. Electron. Comm. Probab. 11 (2006) 149–159. [CrossRef] [MathSciNet] [Google Scholar]
  8. G.H. Hardy, J.E. Littlewood and G. Pólya, Inequalities. Cambridge University Press, 2d ed. (1952). [Google Scholar]
  9. A. Kolmogoroff, Sur la notion de la moyenne. Rendiconti Accad. d. L. Roma 12 (1930) 388–391. [Google Scholar]
  10. T.L. Lai and Q.-M. Shao, Self-normalized limit theorems in probability and statistics, in Asymptotic theory in probability and statistics with applications, Int. Press, Somerville, MA Adv. Lect. Math. (ALM) 2 (2008) 3–43. [Google Scholar]
  11. Y. Nikitin, Asymptotic efficiency of non parametric tests. Cambridge University Press (1995). [Google Scholar]
  12. M. Nagumo, Über eine Klasse der Mittelwerte. Japan. J. Math. 7 (1930) 71–79. [Google Scholar]
  13. E. Porcu, J. Mateu and G. Christakos, Quasi-arithmetic means of covariance functions with potential applications to space-time data. J. Multivar. Anal. 100 (2009) 1830–1844. [CrossRef] [Google Scholar]
  14. Q.-M. Shao, Self-normalized large deviations. Ann. Probab. 25 (1997) 285–328. [CrossRef] [MathSciNet] [Google Scholar]
  15. Q.-M. Shao, A note on the self-normalized large deviation. Chinese J. Appl. Probab. Statist. 22 (2006) 358–362. [MathSciNet] [Google Scholar]
  16. A.V. Tchirina, Large deviations for a class of scale-free statistics under the gamma distribution. J. Math. Sci. 128 (2005) 2640–2655. [CrossRef] [MathSciNet] [Google Scholar]
  17. R.R. Yager, On ordered weighted averaging aggregation operators in multicriteria decisionmaking. IEEE Trans. Systems Man Cybernet. 18 (1988) 183–190. [CrossRef] [MathSciNet] [Google Scholar]

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