J. Beran, Statistics for long-memory processes, of Monographs on Statistics and Applied Probability. Chapman and Hall, 1994.

P. Billingsley, Probability and measure, 1995.

P. Bondon and W. Palma, A Class of Antipersistent Processes, Journal of Time Series Analysis, vol.81, issue.2, pp.261-273, 2007.
DOI : 10.1103/PhysRevE.68.017103

R. Dahlhaus, Efficient Parameter Estimation for Self-Similar Processes, The Annals of Statistics, vol.17, issue.4, pp.1749-1766, 1989.
DOI : 10.1214/aos/1176347393

R. Dahlhausann and . Statist, Efficient Parameter Estimation for Self-Similar Processes, The Annals of Statistics, vol.17, issue.4, pp.1749-17661045, 1989.
DOI : 10.1214/aos/1176347393

M. Falk, Local asymptotic normality in a stationary model for spatial extremes, Journal of Multivariate Analysis, vol.102, issue.1, pp.48-60, 2011.
DOI : 10.1016/j.jmva.2010.07.012

R. Fox and M. S. Taqqu, Central limit theorems for quadratic forms in random variables having long-range dependence. Probab. Theory Related Fields, pp.213-240, 1987.

B. Garel and M. Hallin, Local asymptotic normality of multivariate ARMA processes with a linear trend, Ann. Inst. Statist. Math, vol.47, issue.3, pp.551-579, 1995.

C. W. Granger and R. Joyeux, AN INTRODUCTION TO LONG-MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCING, Journal of Time Series Analysis, vol.7, issue.1, pp.15-29, 1980.
DOI : 10.2307/3212527

A. Franklin and . Graybill, Matrices with applications in statistics Wadsworth Statistics/Probability Series, 1983.

J. R. Hosking, Fractional differencing, Biometrika, vol.68, issue.1, pp.165-176, 1981.
DOI : 10.1093/biomet/68.1.165

A. N. Kolmogorov, Wienersche Spiralen und einige andere interessante Kurven in Hilbertsche Raum, C. R. (Dokl.) Acad. Sci. URSS, vol.26, pp.115-118, 1940.

D. Lai, X. Wang, and J. Wiorkowski, Local asymptotic normality for multivariate nonlinear AR processes, Stochastics and Stochastic Reports, vol.49, issue.3-4, pp.3-4277, 2002.
DOI : 10.1080/10451120290019221

L. and L. Cam, Locally asymptotically normal families of distributions. Certain approximations to families of distributions and their use in the theory of estimation and testing hypotheses, Univ. california Publ. Statist, vol.3, pp.37-98, 1960.

O. Lieberman, R. Rosemarin, and J. Rousseau, ASYMPTOTIC THEORY FOR MAXIMUM LIKELIHOOD ESTIMATION OF THE MEMORY PARAMETER IN STATIONARY GAUSSIAN PROCESSES, Econometric Theory, vol.28, issue.02
DOI : 10.1016/S0304-4076(98)00080-3
URL : https://hal.archives-ouvertes.fr/hal-00641474

O. Lieberman, R. Rosemarin, and J. Rousseau, Asymptotic theory for maximum likelihood estimation of the memory parameter in stationary gaussian processes (full version) Available at http

O. Lieberman, J. Rousseau, and D. M. Zucker, Valid asymptotic expansions for the maximum likelihood estimator of the parameter of a stationary, Gaussian, strongly dependent process, Ann. Statist, vol.31, issue.2, pp.586-612, 2003.
URL : https://hal.archives-ouvertes.fr/hal-00171339

J. Loubes and D. Paindaveine, Local asymptotic normality property for lacunar wavelet series. ESAIM: Probability and Statistics, 2011.

B. Mandelbrot and J. Van-ness, Fractional Brownian Motions, Fractional Noises and Applications, SIAM Review, vol.10, issue.4, pp.422-437, 1968.
DOI : 10.1137/1010093

D. Pollard, Convergence of stochastic processes. Springer Series in Statistics, 1984.

G. Samorodnitsky and M. S. Taqqu, Stable non-Gaussian random processes. Stochastic Modeling, 1994.

A. W. Van and . Vaart, Asymptotic statistics, volume 3 of Cambridge Series in Statistical and Probabilistic Mathematics, 1998.

A. Wald, Tests of statistical hypotheses concerning several parameters when the number of observations is large, Transactions of the American Mathematical Society, vol.54, issue.3, pp.426-482, 1943.
DOI : 10.1090/S0002-9947-1943-0012401-3