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All issues Volume 28 (2024) ESAIM: PS, 28 (2024) 292-328 References
Open Access
Issue
ESAIM: PS
Volume 28, 2024
Page(s) 292 - 328
DOI https://doi.org/10.1051/ps/2024010
Published online 10 September 2024
  1. A.-S. Sznitman, Topics in propagation of chaos, in École d’Été de Probabilités de Saint-Flour XIX-1989, Vol. 1464 of Lecture Notes in Mathematics. Springer, Berlin (1991) 165–251. [CrossRef] [Google Scholar]
  2. D. Talay and M. Tomasevic, A stochastic particle method to solve the parabolic-parabolic Keller–Segel system: an algorithmic and numerical study. (2022) submitted for publication. [Google Scholar]
  3. D.L. Hawkins, Can the finiteness of a mean be tested? Stat. Probab. Lett. 32 (1997) 273–277. [CrossRef] [Google Scholar]
  4. H. Olivero and D. Talay, Supplementary material to “a hypothesis test for the domain of attraction of a random variable”. https://hal.science/hal-04266438 (2023). [Google Scholar]
  5. D.R. Holt and E.L. Crow, Tables and graphs of the stable probability density functions. J. Res. Natl. Bureau Standards B 77 (1973). [Google Scholar]
  6. W. Feller, An Introduction to Probability Theory and Its Applications. Vol. 2 of An Introduction to Probability Theory and Its Applications. Wiley (1971). [Google Scholar]
  7. P. Embrechts, C. Klüppelberg and T. Mikosch, Modelling Extremal Events: for Insurance and Finance. Stochastic Modelling and Applied Probability. Springer Berlin Heidelberg (1997). [Google Scholar]
  8. W. Whitt, Stochastic-process Limits: An Introduction to Stochastic-Process Limits and their Application to Queues. Springer Science & Business Media (2002). [CrossRef] [Google Scholar]
  9. S. Qiman, An invariance principle for stationary p-mixing sequences with infinite variance. Chinese Ann. Math. B 14 (1993) 27–42. [Google Scholar]
  10. M. Tyran-Kamińska, Convergence to lévy stable processes under some weak dependence conditions. Stochastic Processes Appl. 120 (2010) 1629–1650. [CrossRef] [MathSciNet] [Google Scholar]
  11. J. Jacod and A. Shiryaev, Limit Theorems for Stochastic Processes, Vol. 288. Springer Science & Business Media (2013). [Google Scholar]
  12. Y. Aït-Sahalia and J. Jacod, Testing for jumps in a discretely observed process. Ann. Stat. 37 (2009) 184–222. [Google Scholar]
  13. O.E Barndorff-Nielsen and N. Shephard, Econometrics of testing for jumps in financial economics using bipower variation. J. Financ. Econ. 4 (2006) 1–30. [Google Scholar]
  14. J. Jurečková and J. Picek, A class of tests on the tail index. Extremes 4 (2001) 165–183. [CrossRef] [MathSciNet] [Google Scholar]
  15. N. Markovich, Nonparametric Analysis of Univariate Heavy-tailed Data: Research and Practice. John Wiley & Sons (2008). [Google Scholar]
  16. J. Bertoin, Lévy Processes, Vol. 121. Cambridge University Press (1998). [Google Scholar]
  17. P. Embrechts and C.M. Goldie, On closure and factorization properties of subexponential and related distributions. J. Austr. Math. Soc. 29 (1980) 243–256. [CrossRef] [Google Scholar]
  18. W. Hoeffding and H. Robbins, The central limit theorem for dependent random variables. Duke Math. J. 15 (1948) 773–780. [CrossRef] [MathSciNet] [Google Scholar]
  19. J. Jurečková and J. Kalina, Nonparametric multivariate rank tests and their unbiasedness. Bernoulli 18 (2012) 229–251. [MathSciNet] [Google Scholar]
  20. J.P. Nolan, Univariate Stable Distributions, Vol. 10. Springer (2020). [CrossRef] [Google Scholar]
  21. S.K. Basu, M. Maejima and N.K. Patra, A non-uniform rate of convergence in a local limit theorem concerning variables in the domain of normal attraction of a stable law. Yokohama Math. J. 27 (1979) 63–72. [MathSciNet] [Google Scholar]
  22. J.M. Gairing and P. Imkeller, Stable clts and rates for power variation of α-stable Lévy processes. Methodol. Comput. Appl. Probab. 17 (2015) 73–90. [CrossRef] [MathSciNet] [Google Scholar]
  23. F. Avram and M.S. Taqqu, Weak convergence of sums of moving averages in the α-stable domain of attraction. Ann. Probab. 20 (1992) 483–503. [CrossRef] [MathSciNet] [Google Scholar]

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