Estimation of anisotropic gaussian fields through Radon transform
ESAIM: Probability and Statistics, Tome 12 (2008), pp. 30-50.

We estimate the anisotropic index of an anisotropic fractional brownian field. For all directions, we give a convergent estimator of the value of the anisotropic index in this direction, based on generalized quadratic variations. We also prove a central limit theorem. First we present a result of identification that relies on the asymptotic behavior of the spectral density of a process. Then, we define Radon transforms of the anisotropic fractional brownian field and prove that these processes admit a spectral density satisfying the previous assumptions. Finally we use simulated fields to test the proposed estimator in different anisotropic and isotropic cases. Results show that the estimator behaves similarly in all cases and is able to detect anisotropy quite accurately.

DOI : 10.1051/ps:2007031
Classification : 60G60, 62M40, 60G15, 60G10, 60G17, 60G35, 44A12
Mots clés : anisotropic gaussian fields, identification, estimator, asymptotic normality, Radon transform
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     title = {Estimation of anisotropic gaussian fields through {Radon} transform},
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     language = {en},
     url = {http://www.numdam.org/articles/10.1051/ps:2007031/}
}
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Biermé, Hermine; Richard, Frédéric. Estimation of anisotropic gaussian fields through Radon transform. ESAIM: Probability and Statistics, Tome 12 (2008), pp. 30-50. doi : 10.1051/ps:2007031. http://www.numdam.org/articles/10.1051/ps:2007031/

[1] P. Abry and F. Sellan, The wavelet-based synthesis for fractional Brownian motion proposed by F. Sellan and Y. Meyer: remarks and fast implementation. Appl. Comput. Harmon. Anal. 3 (1996) 377-383. | MR | Zbl

[2] A. Ayache, A. Bonami and A. Estrade, Identification and series decomposition of anisotropic Gaussian fields. Proceedings of the Catania ISAAC05 congress (2005).

[3] J.M. Bardet, G. Lang, G. Oppenheim, A. Philippe, S. Stoev and M.S. Taqqu, Semi-parametric estimation of the long-range dependence parameter: a survey. In Theory and applications of long-range dependence, Birkhäuser Boston (2003) 557-577. | MR | Zbl

[4] A. Begyn, Asymptotic development and central limit theorem for quadratic variations of gaussian processes. To appear in Bernoulli (2006). | MR | Zbl

[5] A. Benassi, S. Cohen, J. Istas and S. Jaffard, Identification of filtered white noises. Stochastic Process. Appl. 75 (1998) 31-49. | MR | Zbl

[6] A. Benassi, S. Jaffard and D. Roux, Elliptic Gaussian random processes. Rev. Mathem. Iberoamericana. 13 (1997) 19-89. | EuDML | MR | Zbl

[7] H. Biermé, Champs aléatoires : autosimilarité, anisotropie et étude directionnelle2005).

[8] A. Bonami and A. Estrade, Anisotropic analysis of some Gaussian models. J. Fourier Anal. Appl. 9 (2003) 215-236. | MR | Zbl

[9] G. Chan, An effective method for simulating Gaussian random fields, in Proceedings of the statistical Computing section, 133-138, www.stat.uiowa.edu/grchan/ (1999). Amerir. Statist.

[10] J.F. Coeurjolly, Inférence statistique pour les mouvements browniens fractionnaires et multifractionnaires. PhD thesis, Université Joseph Fourier (2000).

[11] J.F. Coeurjolly, Estimating the parameters of fractional Brownian motion by discrete variations of its sample paths. Stat. Inference Stoch. Process. 4 (2001) 199-227. | MR | Zbl

[12] D. Dacunha-Castelle and M. Duflo, Probabilités et statistiques, Vol. 2. Masson (1983). | MR | Zbl

[13] C.R. Dietrich and G.N. Newsam, Fast and exact simulation of stationary gaussian processes through circulant embedding of the covariance matrix. SIAM J. Sci. Comput. 18 (1997) 1088-1107. | MR | Zbl

[14] N. Enriquez, A simple construction of the fractional brownian motion. Stochastic Process. Appl. 109 (2004) 203-223. | MR | Zbl

[15] J. Istas and G. Lang, Quadratic variations and estimation of the local Hölder index of a Gaussian process. Ann. Inst. Henri Poincaré, Prob. Stat. 33 (1997) 407-436. | Numdam | MR | Zbl

[16] R. Jennane, R. Harba, E. Perrin, A. Bonami and A. Estrade, Analyse de champs browniens fractionnaires anisotropes2001) 99-102.

[17] L.M. Kaplan and C.C.J. Kuo, An Improved Method for 2-d Self-Similar Image Synthesis. IEEE Trans. Image Process. 5 (1996) 754-761.

[18] J.T. Kent and A.T.A. Wood, Estimating the fractal dimension of a locally self-similar Gaussian process by using increments. J. Roy. Statist. Soc. Ser. B 59 (1997) 679-699. | MR | Zbl

[19] G. Lang and F. Roueff, Semi-parametric estimation of the Hölder exponent of a stationary Gaussian process with minimax rates. Stat. Inference Stoch. Process. 4 (2001) 283-306. | MR | Zbl

[20] S. Leger, Analyse stochastique de signaux multi-fractaux et estimations de paramètres. Ph.D. thesis, Université d'Orléans, http://www.univ-orleans.fr/mapmo/publications/leger/these.php (2000).

[21] B.B. Mandelbrot and J. Van Ness, Fractional Brownian motion, fractionnal noises and applications. Siam Review 10 (1968) 422-437. | MR | Zbl

[22] Y. Meyer, F. Sellan and M.S. Taqqu, Wavelets, Generalised White Noise and Fractional Integration: The Synthesis of Fractional Brownian Motion. J. Fourier Anal. Appl. 5 (1999) 465-494. | MR | Zbl

[23] I. Norros and P. Mannersalo, Simulation of Fractional Brownian Motion with Conditionalized Random Midpoint Displacement. Technical report, Advances in Performance analysis, http://vtt.fi/tte/tte21:traffic/rmdmn.ps (1999).

[24] R.F. Peltier and J. Lévy Véhel, Multifractional Brownian motion: definition and preliminary results. Technical report, INRIA, http://www.inria.fr/rrrt/rr-2645.html (1996).

[25] E. Perrin, R. Harba, C. Berzin-Joseph, I. Iribarren and A. Bonami, nth-order fractional Brownian motion and fractional Gaussian noises. IEEE Trans. Sign. Proc. 45 (2001) 1049-1059.

[26] E. Perrin, R. Harba, R. Jennane and I. Iribarren, Fast and Exact Synthesis for 1-D Fractional Brownian Motion and Fractional Gaussian Noises. IEEE Signal Processing Letters 9 (2002) 382-384.

[27] V. Pipiras, Wavelet-based simulation of fractional Brownian motion revisited. Preprint, http://www.stat.unc.edu/faculty/pipiras (2004). | MR | Zbl

[28] A.G. Ramm and A.I. Katsevich, The Radon Transform and Local Tomography. CRC Press (1996). | MR | Zbl

[29] M.L. Stein, Fast and exact simulation of fractional Brownian surfaces. J. Comput. Graph. Statist. 11 (2002) 587-599. | MR

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