@phdthesis{BJHTUP11_1997__0466__A1_0, author = {Bardet, Jean-Marc}, title = {Tests d'autosimilarit\'e des processus gaussiens : dimension fractale et dimension de corr\'elation}, series = {Th\`eses d'Orsay}, publisher = {Universit\'e de Paris-Sud U.F.R. Scientifique d'Orsay}, number = {466}, year = {1997}, language = {fr}, url = {http://archive.numdam.org/item/BJHTUP11_1997__0466__A1_0/} }
TY - BOOK AU - Bardet, Jean-Marc TI - Tests d'autosimilarité des processus gaussiens : dimension fractale et dimension de corrélation T3 - Thèses d'Orsay PY - 1997 IS - 466 PB - Université de Paris-Sud U.F.R. Scientifique d'Orsay UR - http://archive.numdam.org/item/BJHTUP11_1997__0466__A1_0/ LA - fr ID - BJHTUP11_1997__0466__A1_0 ER -
%0 Book %A Bardet, Jean-Marc %T Tests d'autosimilarité des processus gaussiens : dimension fractale et dimension de corrélation %S Thèses d'Orsay %D 1997 %N 466 %I Université de Paris-Sud U.F.R. Scientifique d'Orsay %U http://archive.numdam.org/item/BJHTUP11_1997__0466__A1_0/ %G fr %F BJHTUP11_1997__0466__A1_0
Bardet, Jean-Marc. Tests d'autosimilarité des processus gaussiens : dimension fractale et dimension de corrélation. Thèses d'Orsay, no. 466 (1997), 116 p. http://numdam.org/item/BJHTUP11_1997__0466__A1_0/
[1] Geometry of random fields. Wiley, New York. | MR | Zbl
(1981).[2] Problèmes ergodiques de la mécanique classique.. Gauthier-Villars, Paris. | MR | Zbl
et (1967).[3] Evidence of chaotic dynamics of brain activity during the sleep cycle. Phys. Letters 111 152-156. | DOI
, et (1985).[4] Chaos with confidence : asymptotics and applications of local Lyapunov expnonents. In Fields Institute Communications 11 115-133 | MR | Zbl
, et (1997).[5] Chance or chaos ? J. R. Statist. Soc. A 153 321-347. | DOI
(1990).[6] The dynamics of the Hénon map. Ann. Math. 133 73-169. | MR | Zbl | DOI
and (1991).[7] L'ordre dans le chaos. Herman, Paris.
, , et (1984).[8] Optimal asymptotic quadratic error of density estimators for strong mixing or chaotic data. J. Stat. Probab. Lett. 22 339-347. | MR | Zbl | DOI
(1995).[9] Non parametric estimation of the chaotic function and the invariant measure of a dynamical system. J. Stat. Probab. Lett. 25 201-212. | MR | Zbl | DOI
et (1995).[10] Chaos and deterministic versus stochastic non-linear modelling. J. R. Statist. Soc. B 54 303-328. | MR
(1992).[11] On consistent nonparametric order determination and chaos. J. R. Statist. Soc. B 54 427-449. | MR | Zbl
et (1992).[12] Some results on the behavior and estimation of the fractal dimensions of distributions on attractors. J. Statist. Phys. 62 651-708. | MR | Zbl | DOI
(1991).[13] A theory of correlation dimension for stationary time series. Philos. Trans. R. Soc. Lond. A 348 343-355. | MR | Zbl | DOI
(1994).[14] Chaos et déterminisme. Seuil : Points sciences.
, et (1992).[15] Rigorous statistical procedure for data from dynamical systems. J. Statist. Phys. 49 67-93. | MR | Zbl | DOI
et (1986).[16] Estimating correlation dimension from a chaotic time series : when does plateau onset occur ? Physica D 69 404-424. | MR | Zbl
, , , , and (1993).[17] Ergodic theory of chaos and strange attractors. Rev. Mod. Phys. 57 617-656. | MR | Zbl | DOI
and (1985).[18] Fractal geometry. Chichester : Wiley. | MR
(1990).[19] The transition to aperiodic behavior in turbulent systems. Comm. Math. Phys. 77 65-86. | MR | Zbl | DOI
(1980).[20] Quasiperiodicity in dissipative systems: a renormalizion group analysis. Physica D 5 370-386. | MR
, and (1982).[21] Estimating the correlation dimension of an attractor from noisy and small datasets based on re-embedding. Physica D 65 373-398 | MR | Zbl
and (1993).[22] La théoris du chaos. Flammarion : Champs.
(1991).[23] Measuring the strangeness of strange attractors. Physica D 9 189-208. | MR | Zbl
and (1983).[24] Nonlinear oscillations, dynamical systems, and bifurcations of vector fields. | MR | Zbl
and (1986).[25] A two dimensional mapping with a strange attractor. Comm. Math. Phys. 50 69-77. | MR | Zbl | DOI
(1976).[26] Statistical aspects of chaos: a review. Networks and Chaos - Statistical and probabilistic aspects - Chapman and Hall, London, 124-200. | MR | Zbl
(1993).[27] Chaotic dynamical systems with a view towards statistics : a review. Networks and Chaos- Statistical and probabilistic aspects Chapman and Hall, London, 201-250. | MR | Zbl
. (1993).[28] La structure des révolutions scientifiques. Flammarion : Champs.
(1983).[29] Estimating local Lyapunov exponents. In Fields Institute Communications 11 135-151 | MR | Zbl
et (1997).[30] Estimating the Lyapunov exponent of a chaotic system with non-parametric regression. J. Am. Statist. Ass. 86 682-695 | MR | Zbl | DOI
, , et (1992).[31] Les objects fractals. Flammarion : Champs.
(1995).[32] Dimension of strange attractors: an experimental determination for the chaotic regime of two convective systems. J. Phys. Lett. 44 L-897. | DOI
, , et (1984).[33] Noise reduction in chaotic time series using scaled probabilistic methods. J. Nonlinear Sci. 1 313-343. | MR | Zbl | DOI
and (1991).[34] Dimensions and entropies in chaotic systems. New-York : Springer-Verlag. | MR | Zbl | DOI
(1986).[35] Finding chaos in noisy systems. J. R. Stat. Soc. B 54 399-426. | MR
, , and (1992).[36] Maximum likelihood estimates of the fractal dimension for random spatial patterns. Biometrika 78 463-474. | MR | Zbl | DOI
and (1991).[37] Statistical properties of chaotic systems. Bull. Am. Math. Soc. 24 11-116. | MR | Zbl | DOI
and (1991).[38] Finite correlation dimension for stochastic systems with power-law spectra. Physica D 35 357-381. | MR | Zbl
and (1989).[39] On rigorous mathematical definitions of correlation dimension and generalized spectrum for dimensions. J. Statist. Phys. 71 529-547. | MR | Zbl | DOI
(1993).[40] La nouvelle alliance. Gallimard : Folio essais..
et (1986).[41] Deterministic chaos versus random noise : finite correlation dimension for colored noises with power-law power spectra. 260-275. | MR
and (1991).[42] Probability theory.. | MR | Zbl
(1970).[43] Comm. Math. Phys. 82 137-151. | MR | Zbl | DOI
et , (1971)..[44] Small random perturbations of dynamical systems and the definition of attractors. Comm. Math. Phys. 82 137-151. | MR | Zbl | DOI
(1981).[45] Chaotic evolution and strange attractors. Cambridge : Cambridge University Press. | MR | Zbl
(1989a).[46] Elements of differentiable dynamics and bifurcation theory. New-York : Academic Press. | MR | Zbl
(1989b).[47] Deterministic chaos : the science and the fiction. Proc. R. Soc. Lond. B 427 241-248. | Zbl | MR
(1990).[48] Hasard et chaos Odile Jacob : Points.
(1991).[49] Nonlinear dynamics in economics and finance. Philos. Trans. R. Soc. Lond. A 346 235-250. | MR | Zbl | DOI
(1994).[50] A consistent approach to least squares estimation of correlation dimension in weak Bernoulli dynamical systems. Annals Appl. Probab. 4 1234-1254. | MR | Zbl | DOI
(1994).[51] Optimal estimation of fractal dimension. In Nonlinear modeling and forecasting, Proc. Vol. XII, Eds. M. Casdagli and S. Eubank, Addison-Wesley.
(1992).[52] Estimating dimension in noisy chaotic time series. J. R. Stat. Soc. B 54 329-351. | MR | Zbl
(1992).[53] Lacunarity in a best estimator of fractal dimension. Physics Letters A 133 195-200. | MR | DOI
(1988).[54] Statistical precision of dimension estimators. Physical Review A 41 3038-3051. | DOI
(1990).[55] Some comments on the correlation dimension of noise. Physics Letters A 155 480-493. | MR | DOI
(1991).[56] Nonlinear Times Series. Oxford, Oxford Univ. Press. | MR
(1990).[57] Determining Lyapunov exponents from a time series. Physica D 16 285-315. | MR | Zbl
, , and (1985).[58] Local Lyapunov exponents : looking closely at chaos. J. R. Stat. Soc. B 54 353-371. | MR
(1992).[59] Dimension, entropy and Lyapunov exponents. Ergod. Theory Dynam. Syst. 2 109-124. | MR | Zbl | DOI
(1982).[1] Geometry of random fields. Wiley, New York. | MR | Zbl
(1981).[2] Local non-determinism and local times of Gaussian processes. Indiana Math. J. 23 69-94. | MR | Zbl | DOI
(1973).[3] A theory of correlation dimension for stationary time series. Philos. Trans. R. Soc. Lond. A 348 343-355. | MR | Zbl | DOI
(1994).[4] Some local properties of Gaussian vector fields. Ann. Probab. 6 984-994. | MR | Zbl | DOI
(1978).[5] Multiple points of a Gaussian vector fields. Z. Warsch. Verw. Gebiete 61 431-436. | MR | Zbl | DOI
(1982).[6] Estimating correlation dimension from a chaotic time series : when does plateau onset occur ? Physica D 69 404-424. | MR | Zbl
, , , , and (1993).[7] Self-intersection gauge for random walks and for Brownian motion. Ann. Probab. 16 1-57. | MR | Zbl
(1988).[8] Ergodic theory of chaos and strange attractors. Rev. Mod. Phys. 57 617-656. | MR | Zbl | DOI
and (1985).[9] An introduction to probability theory and its applications. Vol. 2, Wiley. | MR
(1971).[10] Potemtiel d'équilibre et capacité des ensembles, avec quelques applications à la théorie des fonctions. Medd. Lunds. Univ. Mat. Semin. 3. | JFM
(1935).[11] Occupation densities. Ann. Probab. 8 1-67. | MR | Zbl | DOI
and (1980).[12] Measuring the strangeness of strange attractors. Physica D 9 189-208. | MR | Zbl
and (1983).[13] Chaos expansions of double intersection local time of Brownian motion in and renormalization. Stock. Pro. Appl. 56 1-34. | MR | Zbl | DOI
, and (1995).[14] On Hausdorff's measures and generalized capacities with some of their applications to the theory of functions. Japanese J. Math. 19 217-257. | MR | Zbl | DOI
(1944).[15] Double points of a Gaussian path. Z. Warsch. Verw. Gebiete 45 175-180. | MR | Zbl | DOI
(1978).[16] Sur le temps local d'intersection du mouvement brownien plan et la méthode de renormalisation de Varadhan. Séminaire de Probabilités XIX. Lecture Notes in Math. 1123 314-331. | MR | Zbl | Numdam
(1985).[17] Local times for Gaussian vector fields. Indiana Univ. Math. J. 27 309-330. | MR | Zbl | DOI
(1978).[18] A local time approach to the self-intersections of Brownian paths in space. Comm. Math. Phys. 88 327-338. | MR | Zbl | DOI
(1983).[19] Self-intersections of random fields. Ann. Probab. 12 108-119. | MR | Zbl | DOI
(1984).[20] The intersection local time of fractional Brownian motion in the plane. J. Mult. Anal. 23 37-46. | MR | Zbl | DOI
(1987).[21] Continuity and singularity of the intersection local time of stable processes in . Ann. Probab. 16 75-79. | MR | Zbl | DOI
(1988).[22] Estimating dimension in noisy chaotic time series. J. R. Stat. Soc. B 54 329-351. | MR | Zbl
(1992).[1] The wavelet-based synthesis for the fractional Brownian motion proposed by F. Sellan and Y. Meyer : remarks and fast implementation. Applied, and Computational Harmonic Analysis 3, 377-383. | MR | Zbl | DOI
and (1996).[2] Séries d'observations irrégulières. Masson, Paris. | MR | Zbl
and (1984).[3] Statistics for long memory processes. Monographs on Statist, and Appl. Probab. 61. Chapman & Hall, 315 p. | MR | Zbl
(1994).[4] Central limit theorem for non-linear functionals of Gaussian fields. J. Multivariate Anal. 13, 425-441. | MR | Zbl | DOI
and (1983).[5] Large-sample properties of parameter estimates for strongly dependent Gaussian time series. Ann. Statist. 14, 517-532. | MR | Zbl
and (1986).[6] Central limits theorems for quadratic forms in random variables having long-range dependence. Probab. Theory Related Fields 74, 213-240. | MR | Zbl | DOI
and (1987).[7] The estimation and application of long memory time series models. J. Time Ser. Anal. 4, 221-238. | MR | Zbl | DOI
and (1983).[8] A central limit theorem for quadratic forms in strongly dependent linear variables and its applications to the asymptotic normality of Whittle estimate. Probab. Theory Related Fields 86, 87-104. | MR | Zbl | DOI
and (1990).[9] Quadratic variations and estimation of the local Holder index of a Gaussian process. Ann. Inst. Poincaré 33, 407-436. | MR | Zbl | Numdam | DOI
and (1997).[10] The fractal geometry of nature. Freeman, San Francisco. | MR | Zbl
(1983).[11] Fractional Brownian motions, fractional noises and applications. SIAM Review 10, 422-437. | MR | Zbl | DOI
and (1968).[12] An estimate of the fractal index using multiscale aggregates. To appear in J. Time Ser. Anal. | MR | Zbl
and (1996).[13] Log-periodogram regression of time series with long-range dependence. Ann. Statist. 23, 1048-1072. | MR | Zbl | DOI
(1995).[14] Stable non-Gaussian random processes. Stochastic modeling. Chapman & Hall, 636 p. | MR | Zbl
and (1994).[15] Weak Convergence to Fractional Brownian Motion and to Rosenblatt Process. Zeit. Wahr. verw. Geb. 31, 287-302. | MR | Zbl | DOI
(1975).[16] Estimators for long-range dependence: an empirical study. Fractals 3, 785-798. | Zbl | DOI
, and (1995).[17] Asymptotic properties of the LSE in a regression model with long-range stationary errors. Ann. Statist. 19, 158-177. | MR | Zbl
(1989).[1] The wavelet-based synthesis for the fractional Brownian motion proposed by F. Sellan and Y. Meyer : remarks and fast implementation. Applied and Computational Harmonic Analysis 3, 377-383. | MR | Zbl | DOI
and (1996).[2] Wavelets, spectrum analysis and processes. Wavelets and Statistics, Lectures Note in Statistics, 103, 15-29. | Zbl
, and (1995).[3] Wavelet analysis of long range dependent traffic. To appear in IEEE Trans, on Inform. Theory. | MR | Zbl
and (1997).[4] Long-range dependence : revisiting aggregation with wavelets. To appear in J. Time Ser. Anal. | MR | Zbl
, and (1997).[5] Testing self-similarity of Gaussian processes with stationary increments. Preprint Orsay.
(1997).[6] Statistics for long memory processes. Monographs on Stat. and Appli. Prob. 61. Chapman & Hall, 315 p. | MR | Zbl
(1994).[7] Ten lectures on wavelets. CBMS, SIAM 61, Philadelphia. | MR | Zbl
(1992).[8] On the spectrum of fractional Brownian motions. IEEE Trans. on Info. Theory 35 197-199. | MR | DOI
(1989).[9] Wavelet analysis and synthesis of fractional Brownian motion. IEEE Trans. on Inform. Theory 38 910-917. | MR | Zbl | DOI
(1992).[10] The estimation and application of long memory time series models. J. Time Ser. Anal. 4, 221-238. | MR | Zbl | DOI
and (1983).[11] A central limit theorem for quadratic forms in strongly dependent linear variables and its applications to the asymptotic normality of Whittle estimate. Probab. Theory Related Fields 86, 87-104. | MR | Zbl | DOI
and (1990).[12] Multiple-window wavelet transform and local scaling exponent estimation. Preprint INRIA.
and (1997).[13] Quadratic variations and estimation of the local Hölder index of a Gaussian process. Ann. Inst. Poincaré 33, 407-436. | MR | Zbl | Numdam | DOI
and (1997).[14] The fractal geometry of nature. Freeman, San Francisco. | MR | Zbl | DOI
(1983).[15] An estimate of the fractal index using multiscale aggregates. To appear in J. Time Ser. Anal. | MR | Zbl
and (1996).[16] Log-periodogram regression of time series with long-range dependence. Ann. Statist. 23, 1048-1072. | MR | Zbl | DOI
(1995).[17] Stable non-Gaussian random processes. Stochastic modeling. Chapman & Hall, 636 p. | MR | Zbl
and (1994).[18] Weak Convergence to Fractional Brownian Motion and to Rosenblatt Process. Z. Wahrscheinlichkeitstheorie verw. Geb. 31, 287-302. | MR | Zbl | DOI
(1975).[19] Estimators for long-range dependence : an empirical study. Fractals 3, 785-798. | Zbl | DOI
, and (1995).[20] Asymptotic properties of the LSE in a regression model with long-range stationary errors. Ann. Statist. 19, 158-177. | MR | Zbl
(1989).