Asymptotic behavior of the empirical process for gaussian data presenting seasonal long-memory

Mohamedou Ould Haye

ESAIM: Probability and Statistics (2002)

  • Volume: 6, page 293-309
  • ISSN: 1292-8100

Abstract

top
We study the asymptotic behavior of the empirical process when the underlying data are gaussian and exhibit seasonal long-memory. We prove that the limiting process can be quite different from the limit obtained in the case of regular long-memory. However, in both cases, the limiting process is degenerated. We apply our results to von–Mises functionals and U -Statistics.

How to cite

top

Haye, Mohamedou Ould. "Asymptotic behavior of the empirical process for gaussian data presenting seasonal long-memory." ESAIM: Probability and Statistics 6 (2002): 293-309. <http://eudml.org/doc/245390>.

@article{Haye2002,
abstract = {We study the asymptotic behavior of the empirical process when the underlying data are gaussian and exhibit seasonal long-memory. We prove that the limiting process can be quite different from the limit obtained in the case of regular long-memory. However, in both cases, the limiting process is degenerated. We apply our results to von–Mises functionals and $U$-Statistics.},
author = {Haye, Mohamedou Ould},
journal = {ESAIM: Probability and Statistics},
keywords = {empirical process; Hermite polynomials; Rosenblatt processes; seasonal long-memory; $U$-statistics; von–Mises functionals},
language = {eng},
pages = {293-309},
publisher = {EDP-Sciences},
title = {Asymptotic behavior of the empirical process for gaussian data presenting seasonal long-memory},
url = {http://eudml.org/doc/245390},
volume = {6},
year = {2002},
}

TY - JOUR
AU - Haye, Mohamedou Ould
TI - Asymptotic behavior of the empirical process for gaussian data presenting seasonal long-memory
JO - ESAIM: Probability and Statistics
PY - 2002
PB - EDP-Sciences
VL - 6
SP - 293
EP - 309
AB - We study the asymptotic behavior of the empirical process when the underlying data are gaussian and exhibit seasonal long-memory. We prove that the limiting process can be quite different from the limit obtained in the case of regular long-memory. However, in both cases, the limiting process is degenerated. We apply our results to von–Mises functionals and $U$-Statistics.
LA - eng
KW - empirical process; Hermite polynomials; Rosenblatt processes; seasonal long-memory; $U$-statistics; von–Mises functionals
UR - http://eudml.org/doc/245390
ER -

References

top
  1. [1] M.A. Arcones, Distributional limit theorems over a stationary Gaussian sequence of random vectors. Stochastic Process. Appl. 88 (2000) 135-159. Zbl1045.60019MR1761993
  2. [2] J.-M. Bardet, G. Lang, G. Oppenheim, A. Philippe and M.S. Taqqu, Generators of long-range processes: A survey, in Long range dependence: Theory and applications, edited by P. Doukhan, G. Oppenheim and M.S. Taqqu (to appear). Zbl1031.65010
  3. [3] P. Billingsley, Convergence of Probability measures. Wiley (1968). Zbl0172.21201MR233396
  4. [4] S. Csörgo and J. Mielniczuk, The empirical process of a short-range dependent stationary sequence under Gaussian subordination. Probab. Theory Related Fields 104 (1996) 15-25. Zbl0838.60030MR1367664
  5. [5] H. Dehling and M.S. Taqqu, The empirical process of some long-range dependent sequences with an application to U -statistics. Ann. Statist. 4 (1989) 1767-1783. Zbl0696.60032MR1026312
  6. [6] H. Dehling and M.S. Taqqu, Bivariate symmetric statistics of long-range dependent observations. J. Statist. Plann. Inference 28 (1991) 153-165. Zbl0737.62042MR1115815
  7. [7] R.L. Dobrushin and P. Major, Non central limit theorems for non-linear functionals of Gaussian fields. Z. Wahrsch. Verw. Geb. 50 (1979) 27-52. Zbl0397.60034MR550122
  8. [8] P. Doukhan and S. Louhichi, A new weak dependence condition and applications to moment inequalities. Stochastic Process Appl. 84 (1999) 313-342. Zbl0996.60020MR1719345
  9. [9] P. Doukhan and D. Surgailis, Functional central limit theorem for the empirical process of short memory linear processes. C. R. Acad. Sci. Paris Sér. I Math. 326 (1997) 87-92. Zbl0948.60012MR1649521
  10. [10] J. Ghosh, A new graphical tool to detect non normality. J. Roy. Statist. Soc. Ser. B 58 (1996) 691-702. Zbl0860.62004MR1410184
  11. [11] L. Giraitis, Convergence of certain nonlinear transformations of a Gaussian sequence to self-similar process. Lithuanian Math. J. 23 (1983) 58-68. Zbl0526.60031MR705726
  12. [12] L. Giraitis and R. Leipus, A generalized fractionally differencing approach in long-memory modeling. Lithuanian Math. J. 35 (1995) 65-81. Zbl0837.62066MR1357812
  13. [13] L. Giraitis and D. Surgailis Central limit theorem for the empirical process of a linear sequence with long memory. J. Statist. Plann. Inference 80 (1999) 81-93. Zbl0943.60035MR1713796
  14. [14] I.S. Gradshteyn and I.M. Ryzhik, Table of integrals, series and products. Jeffrey A. 5th Edition. Academic Press (1994). Zbl0918.65002MR1243179
  15. [15] H.C. Ho and T. Hsing, On the asymptotic expansion of the empirical process of long memory moving averages. Ann. Statist. 24 (1996) 992-1024. Zbl0862.60026MR1401834
  16. [16] I. Karatzas and S.E. Shreve, Brownian motion and stochastic calculus. Springer-Verlag, New York (1988). Zbl0638.60065MR917065
  17. [17] R. Leipus and M.-C. Viano, Modeling long-memory time series with finite or infinite variance: A general approach. J. Time Ser. Anal. 21 (1997) 61-74. Zbl0974.62083MR1766174
  18. [18] C. Newman, Asymptotic independence and limit theorems for positively and negatively dependent random variables. IMS Lecture Notes-Monographs Ser. 5 (1984) 127-140. MR789244
  19. [19] G. Oppenheim, M. Ould Haye and M.-C. Viano, Long memory with seasonal effects. Statist. Inf. Stoch. Proc. 3 (2000) 53-68. Zbl0979.60011MR1819286
  20. [20] M. Ould Haye, Longue mémoire saisonnière et convergence vers le processus de Rosenblatt. Pub. IRMA, Lille, 50-VIII (1999). 
  21. [21] M. Ould Haye, Asymptotic behavior of the empirical process for seasonal long-memory data. Pub. IRMA, Lille, 53-V (2000). 
  22. [22] M. Ould Haye and M.-C. Viano, Limit theorems under seasonal long-memory, in Long range dependence: Theory and applications, edited by P. Doukhan, G. Oppenheim and M.S. Taqqu (to appear). Zbl1033.60028MR1956045
  23. [23] D.W. Pollard, Convergence of Stochastic Processes. Springer, New York (1984). Zbl0544.60045MR762984
  24. [24] M. Rosenblatt, Limit theorems for transformations of functionals of Gaussian sequences. Z. Wahrsch. Verw. Geb. 55 (1981) 123-132. Zbl0447.60016MR608012
  25. [25] Q. Shao and H. Yu, Weak convergence for weighted empirical process of dependent sequences. Ann. Probab. 24 (1996) 2094-2127. Zbl0874.60006MR1415243
  26. [26] G.R. Shorack and J.A. Wellner, Empirical Processes with Applications to Statistics. Wiley, New York (1986). Zbl1170.62365MR838963
  27. [27] M.S. Taqqu, Weak convergence to fractional Brownian motion and to the Rosenblatt process. Z. Wahrsch. Verw. Geb. 31 (1975) 287-302. Zbl0303.60033MR400329
  28. [28] A. Zygmund, Trigonometric Series. Cambridge University Press (1959). Zbl0085.05601MR107776

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.