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 -Statistics.
Mots clés : empirical process, Hermite polynomials, Rosenblatt processes, seasonal long-memory, $U$-statistics, von-Mises functionals
@article{PS_2002__6__293_0, author = {Haye, Mohamedou Ould}, title = {Asymptotic behavior of the empirical process for gaussian data presenting seasonal long-memory}, journal = {ESAIM: Probability and Statistics}, pages = {293--309}, publisher = {EDP-Sciences}, volume = {6}, year = {2002}, doi = {10.1051/ps:2002016}, mrnumber = {1943152}, language = {en}, url = {http://www.numdam.org/articles/10.1051/ps:2002016/} }
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 SP - 293 EP - 309 VL - 6 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/ps:2002016/ DO - 10.1051/ps:2002016 LA - en ID - PS_2002__6__293_0 ER -
%0 Journal Article %A Haye, Mohamedou Ould %T Asymptotic behavior of the empirical process for gaussian data presenting seasonal long-memory %J ESAIM: Probability and Statistics %D 2002 %P 293-309 %V 6 %I EDP-Sciences %U http://www.numdam.org/articles/10.1051/ps:2002016/ %R 10.1051/ps:2002016 %G en %F PS_2002__6__293_0
Haye, Mohamedou Ould. Asymptotic behavior of the empirical process for gaussian data presenting seasonal long-memory. ESAIM: Probability and Statistics, Tome 6 (2002), pp. 293-309. doi : 10.1051/ps:2002016. http://www.numdam.org/articles/10.1051/ps:2002016/
[1] Distributional limit theorems over a stationary Gaussian sequence of random vectors. Stochastic Process. Appl. 88 (2000) 135-159. | MR | Zbl
,[2] 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). | Zbl
, , , and ,[3] Convergence of Probability measures. Wiley (1968). | MR | Zbl
,[4] The empirical process of a short-range dependent stationary sequence under Gaussian subordination. Probab. Theory Related Fields 104 (1996) 15-25. | MR | Zbl
and ,[5] The empirical process of some long-range dependent sequences with an application to -statistics. Ann. Statist. 4 (1989) 1767-1783. | MR | Zbl
and ,[6] Bivariate symmetric statistics of long-range dependent observations. J. Statist. Plann. Inference 28 (1991) 153-165. | MR | Zbl
and ,[7] Non central limit theorems for non-linear functionals of Gaussian fields. Z. Wahrsch. Verw. Geb. 50 (1979) 27-52. | MR | Zbl
and ,[8] A new weak dependence condition and applications to moment inequalities. Stochastic Process Appl. 84 (1999) 313-342. | MR | Zbl
and ,[9] 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. | MR | Zbl
and ,[10] A new graphical tool to detect non normality. J. Roy. Statist. Soc. Ser. B 58 (1996) 691-702. | MR | Zbl
,[11] Convergence of certain nonlinear transformations of a Gaussian sequence to self-similar process. Lithuanian Math. J. 23 (1983) 58-68. | MR | Zbl
,[12] A generalized fractionally differencing approach in long-memory modeling. Lithuanian Math. J. 35 (1995) 65-81. | MR | Zbl
and , and limit theorem for the empirical process of a linear sequence with long memory. J. Statist. Plann. Inference 80 (1999) 81-93. |[14] Table of integrals, series and products. Jeffrey A. 5th Edition. Academic Press (1994). | MR | Zbl
and ,[15] On the asymptotic expansion of the empirical process of long memory moving averages. Ann. Statist. 24 (1996) 992-1024. | MR | Zbl
and ,[16] Brownian motion and stochastic calculus. Springer-Verlag, New York (1988). | MR | Zbl
and ,[17] Modeling long-memory time series with finite or infinite variance: A general approach. J. Time Ser. Anal. 21 (1997) 61-74. | MR | Zbl
and ,[18] Asymptotic independence and limit theorems for positively and negatively dependent random variables. IMS Lecture Notes-Monographs Ser. 5 (1984) 127-140. | MR
,[19] Long memory with seasonal effects. Statist. Inf. Stoch. Proc. 3 (2000) 53-68. | MR | Zbl
, and ,[20] Longue mémoire saisonnière et convergence vers le processus de Rosenblatt. Pub. IRMA, Lille, 50-VIII (1999).
,[21] Asymptotic behavior of the empirical process for seasonal long-memory data. Pub. IRMA, Lille, 53-V (2000).
,[22] 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). | MR | Zbl
and ,[23] Convergence of Stochastic Processes. Springer, New York (1984). | MR | Zbl
,[24] Limit theorems for transformations of functionals of Gaussian sequences. Z. Wahrsch. Verw. Geb. 55 (1981) 123-132. | MR | Zbl
,[25] Weak convergence for weighted empirical process of dependent sequences. Ann. Probab. 24 (1996) 2094-2127. | MR | Zbl
and ,[26] Empirical Processes with Applications to Statistics. Wiley, New York (1986). | MR
and ,[27] Weak convergence to fractional Brownian motion and to the Rosenblatt process. Z. Wahrsch. Verw. Geb. 31 (1975) 287-302. | MR | Zbl
,[28] Trigonometric Series. Cambridge University Press (1959). | MR | Zbl
,Cité par Sources :