Local Asymptotic Normality Property for Lacunar Wavelet Series multifractal model*
Jean-Michel Loubes; Davy Paindaveine
ESAIM: Probability and Statistics (2012)
- Volume: 15, page 69-82
- ISSN: 1292-8100
Access Full Article
topAbstract
topHow to cite
topLoubes, Jean-Michel, and Paindaveine, Davy. "Local Asymptotic Normality Property for Lacunar Wavelet Series multifractal model*." ESAIM: Probability and Statistics 15 (2012): 69-82. <http://eudml.org/doc/222462>.
@article{Loubes2012,
abstract = {
We consider a lacunar wavelet series function observed with an additive Brownian motion. Such functions are statistically characterized by two
parameters. The first parameter governs the lacunarity of the wavelet
coefficients while the second one governs its intensity. In this paper,
we establish the local and asymptotic normality (LAN) of the model, with respect to this couple of parameters. This enables to prove the optimality of an estimator for the lacunarity parameter, and to build optimal (in the Le Cam sense) tests on the intensity parameter.
},
author = {Loubes, Jean-Michel, Paindaveine, Davy},
journal = {ESAIM: Probability and Statistics},
keywords = {Local asymptotic normality; lacunar wavelet series; local asymptotic normality},
language = {eng},
month = {1},
pages = {69-82},
publisher = {EDP Sciences},
title = {Local Asymptotic Normality Property for Lacunar Wavelet Series multifractal model*},
url = {http://eudml.org/doc/222462},
volume = {15},
year = {2012},
}
TY - JOUR
AU - Loubes, Jean-Michel
AU - Paindaveine, Davy
TI - Local Asymptotic Normality Property for Lacunar Wavelet Series multifractal model*
JO - ESAIM: Probability and Statistics
DA - 2012/1//
PB - EDP Sciences
VL - 15
SP - 69
EP - 82
AB -
We consider a lacunar wavelet series function observed with an additive Brownian motion. Such functions are statistically characterized by two
parameters. The first parameter governs the lacunarity of the wavelet
coefficients while the second one governs its intensity. In this paper,
we establish the local and asymptotic normality (LAN) of the model, with respect to this couple of parameters. This enables to prove the optimality of an estimator for the lacunarity parameter, and to build optimal (in the Le Cam sense) tests on the intensity parameter.
LA - eng
KW - Local asymptotic normality; lacunar wavelet series; local asymptotic normality
UR - http://eudml.org/doc/222462
ER -
References
top- A. Arneodo, E. Bacry, S. Jaffard and J.F. Muzy, Singularity spectrum of multifractal functions involving oscillating singularities. The Journal of Fourier Analysis and Applications 4 (1998) 159–174.
- A. Arneodo, E. Bacry, S. Jaffard and J.F. Muzy, Oscillating singularities and fractal functions. In Spline functions and the theory of wavelets (Montreal, PQ, 1999) , Amer. Math. Soc. Providence, RI (1999) 315–329.
- J.M. Aubry and S. Jaffard, Random wavelet series. Comm. Math. Phys.227 (2002) 483–514.
- E. Bacry, A. Arneodo, U. Frisch, Y. Gagne and E. Hopfinger, Wavelet analysis of fully developed turbulence data and measurement of scaling exponents. In Turbulence and coherent structures (Grenoble, 1989) , Kluwer Acad. Publ. Dordrecht (1989) 203–215.
- Z. Chi, Construction of stationary self-similar generalized fields by random wavelet expansion. Probab. Theory Related Fields121 (2001) 269–300.
- A. Durand, Random wavelet series based on a tree-indexed Markov chain. Comm. Math. Phys.283 (2008) 451–477.
- P. Flandrin, Wavelet analysis and synthesis of fractional Brownian Motion. IEEE Trans. Inform. Theory38 (1992) 910–917.
- F. Gamboa and J.-M. Loubes, Bayesian estimation of multifractal wavelet function. Bernoulli (2005) 34–57.
- F. Gamboa and J.-M. Loubes, Estimation of the parameters of a multifractal wavelet function. Test16 (2007) 383–407.
- C. Genovese and L. Wasserman, Rates of convergence for the Gaussian mixture sieve. Ann. Statist.28 (2000) 1105–1127.
- S. Jaffard, On lacunary wavelet series. The Annals of Applied Probability10 (2000) 313–329.
- B. Lindsay, The geometry of mixture likelihoods: a general theory. Ann. Statist.11 (1983) 86–94.
- G. McLachlan and K. Basford, Mixture models. Inference and applications to clustering. Statistics: Textbooks and Monographs84. Marcel Dekker, Inc., New York (1988).
- S.G. Mallat, Multiresolution approximations and wavelet orthonormal bases of L2(r). Transactions of the American Mathematical Society315 (1989) 69–87.
- D.L. McLeish and C.G. Small, Likelihood methods for the discrimination problem. Biometrika 73 (1986) 397–403.
- Y. Meyer, Ondelettes et Opérateurs . Hermann (1990).
- R.H. Riedi, M.S. Crouse, V.J. Ribeiro and R.G. Baraniuk, A multifractal wavelet model with application to network traffic. Institute of Electrical and Electronics Engineers. Transactions on Information Theory 45 (1999) 992–1018.
- F. Roueff, Almost sure haussdorff dimensions of graphs of random wavelet series. J. Fourier Analysis and App.9 (2003).
- A.R. Swensen, The asymptotic distribution of the likelihood ratio for autoregressive time series with a regression trend. J. Multivariate Anal.16 (1985) 54–70.
- S. van de Geer, Rates of convergence for the maximum likelihood estimator in mixture models. J. Nonparametr. Statist.6 (1996) 293–310.
- A.W. van der Vaart, Asymptotic statistics . Cambridge Series in Statistical and Probabilistic Mathematics. Cambridge University Press, Cambridge (1998). ISBN 0-521-49603-9; 0-521-78450-6.
NotesEmbed ?
topTo embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.