Open Access
Issue
ESAIM: PS
Volume 24, 2020
Page(s) 186 - 206
DOI https://doi.org/10.1051/ps/2019027
Published online 06 March 2020
  1. N. Balakrishnan and J. Glaz, Scan statistics and applications. Birkhäuser Boston, Inc., Boston, MA (1999). [Google Scholar]
  2. S.N. Bernstein, Quelques remarques sur le théorème limite Liapounoff. Dokl. Akad. Nauk. SSSR 24 (1939) 3–8. [Google Scholar]
  3. P. Billingsley, Convergence of probability measures. Wiley, New York (1968). [Google Scholar]
  4. N.H. Bingham, C.M. Goldie, and J.L. Teugels, Regular variation. Encyclopaedia of Mathematics and its Applications. Cambridge University Press (1987). [Google Scholar]
  5. Z. Ciesielski, On the isomorphisms of the spaces hα and m. Bull. Acad. Pol. Sci. Ser. Sci. Math. Phys. 8 (1960) 217–222. [Google Scholar]
  6. W. Feller, Vol. 2 of An Introduction to Probability Theory and Its Applications. Wiley, second edition (1971). [Google Scholar]
  7. D. Hamadouche and Ch. Suquet, Optimal Hölderian functional central limit theorem for uniform empirical and quantile processes. Math. Methods Stat. 15 (2006) 207–223. [Google Scholar]
  8. J. Markevičiūtė, A. Račkauskas and Ch. Suquet, Functional central limit theorems for sums of nearly nonstationary processes. Lithuanian Math. J. 52 (2012) 282–296. [CrossRef] [Google Scholar]
  9. T. Mikosch and A. Račkauskas The limit distribution of the maximum increment of a random walk with regularly varying jump sizedistribution. Bernoulli 16 (2010) 1016–1038. [CrossRef] [Google Scholar]
  10. V. Pozdnyakov, S. Wallenstein and J. Glaz, Scan statistics : methods and applications. Birkhäuser Boston, Inc., Boston, MA (2009). [Google Scholar]
  11. S.T. Rachev, Probability metrics and the stability of stochastic models. Wiley (1991). [Google Scholar]
  12. A. Račkauskas and Ch. Suquet, Necessary and sufficient condition for the Lamperti invariance principle. Theory Prob. Math. Stat. 68 (2003) 115–124. [Google Scholar]
  13. A. Račkauskas and Ch. Suquet, Necessary and sufficient condition for the Hölderian functional central limit theorem. J. Theor. Prob. 17 (2004) 221–243. [CrossRef] [MathSciNet] [Google Scholar]
  14. A. Račkauskas and Ch. Suquet, Hölder norm test statistics for epidemic change. J. Stat. Plan. Inference 126 (2004) 495–520. [Google Scholar]
  15. G.R. Shorack and J.A. Wellner, Empirical processes with applications to statistics. John Wiley & Sons, New York (1986). [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.