The Annals of Statistics

Consistent estimates of deformed isotropic Gaussian random fields on the plane

Ethan Anderes and Sourav Chatterjee
Source: Ann. Statist. Volume 37, Number 5A (2009), 2324-2350.

Abstract

This paper proves fixed domain asymptotic results for estimating a smooth invertible transformation f: ℝ2→ℝ2 when observing the deformed random field Zf on a dense grid in a bounded, simply connected domain Ω, where Z is assumed to be an isotropic Gaussian random field on ℝ2. The estimate is constructed on a simply connected domain U, such that ⊂Ω and is defined using kernel smoothed quadratic variations, Bergman projections and results from quasiconformal theory. We show, under mild assumptions on the random field Z and the deformation f, that Rθf+c uniformly on compact subsets of U with probability one as the grid spacing goes to zero, where Rθ is an unidentifiable rotation and c is an unidentifiable translation.

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Primary Subjects: 60G60, 62M30, 62M40
Secondary Subjects: 62G05
Full-text: Open access
Links and Identifiers

Permanent link to this document: http://projecteuclid.org/euclid.aos/1247663757
Digital Object Identifier: doi:10.1214/08-AOS647
Zentralblatt MATH identifier: 05596903
Mathematical Reviews number (MathSciNet): MR2543694

References

[1] Adler, R. J. and Pyke, R. (1993). Uniform quadratic variation for Gaussian processes. Stochastic Process. Appl. 48 191–209.
Mathematical Reviews (MathSciNet): MR1244542
Zentralblatt MATH: 0783.60040
Digital Object Identifier: doi:10.1016/0304-4149(93)90044-5
[2] Ahlfors, L. V. (2006). Lectures on Quasiconformal Mappings. University Lecture Series 38 Amer. Math. Soc., Providence, RI.
Mathematical Reviews (MathSciNet): MR2241787
[3] Anderes, E. B. (2005). Estimating deformations of isotropic Gaussian random fields. Ph.D. thesis, Univ. Chicago.
Mathematical Reviews (MathSciNet): MR2717272
Zentralblatt MATH: 1133.62077
[4] Anderes, E. B. and Chatterjee, S. (2008). Consistent estimates of deformed isotropic Gaussian random fields on the plane. Technical Report 739, Statistics Dept., Univ. California at Berkeley. Available at http://www.stat.berkeley.edu/tech-reports/739.pdf.
Mathematical Reviews (MathSciNet): MR2543694
Zentralblatt MATH: 1171.62056
Digital Object Identifier: doi:10.1214/08-AOS647
Project Euclid: euclid.aos/1247663757
[5] Anderes, E. B. and Stein, M. L. (2008). Estimating deformations of isotropic Gaussian random fields on the plane. Ann. Statist. 36 719–741.
Mathematical Reviews (MathSciNet): MR2396813
Zentralblatt MATH: 1133.62077
Digital Object Identifier: doi:10.1214/009053607000000893
Project Euclid: euclid.aos/1205420517
[6] Baxter, G. (1956). A strong limit theorem for Gaussian processes. Proc. Amer. Math. Soc. 7 522–527.
Mathematical Reviews (MathSciNet): MR90920
Zentralblatt MATH: 0070.36304
Digital Object Identifier: doi:10.1090/S0002-9939-1956-0090920-6
[7] Benassi, A., Cohen, S., Istas, J. and Jaffard, S. (1998). Identification of filtered white noises. Stochastic Process. Appl. 75 31–49.
Mathematical Reviews (MathSciNet): MR1629014
Zentralblatt MATH: 0932.60037
Digital Object Identifier: doi:10.1016/S0304-4149(97)00123-3
[8] Berman, S. M. (1967). A version of the Lévy–Baxter theorem for the increments of Brownian motion of several parameters. Proc. Amer. Math. Soc. 18 1051–1055.
Mathematical Reviews (MathSciNet): MR222958
[9] Clerc, M. and Mallat, S. (2002). The texture gradient equation for recovering shape from texture. IEEE Trans. on Pattern Analysis and Machine Intelligence 24 536–549.
[10] Clerc, M. and Mallat, S. (2003). Estimating deformations of stationary processes. Ann. Statist. 31 1772–1821.
Mathematical Reviews (MathSciNet): MR2036390
Zentralblatt MATH: 1052.62086
Digital Object Identifier: doi:10.1214/aos/1074290327
Project Euclid: euclid.aos/1074290327
[11] Cohen, S., Guyon, X., Perrin, O. and Pontier, M. (2006). Identification of an isometric transformation of the standard Brownian sheet. J. Statist. Plann. Inference 136 1317–1330.
Mathematical Reviews (MathSciNet): MR2253765
Zentralblatt MATH: 1089.60047
Digital Object Identifier: doi:10.1016/j.jspi.2004.09.012
[12] Cohen, S., Guyon, X., Perrin, O. and Pontier, M. (2006). Singularity functions for fractional processes: Application to the fractional Brownian sheet. Ann. Inst. H. Poincaré. Probab. Statist. 42 187–205.
Mathematical Reviews (MathSciNet): MR2199797
Zentralblatt MATH: 1095.60011
Digital Object Identifier: doi:10.1016/j.anihpb.2005.03.002
[13] Damian, D., Sampson, P. and Guttorp, P. (2001). Bayesian estimation of semi-parametric non-stationary spatial covariance structures. Environmetrics 12 161–178.
[14] Dieudonné, J. (1960). Foundations of Modern Analysis. Academic Press, New York.
Mathematical Reviews (MathSciNet): MR120319
[15] Dudley, R. M. (1973). Sample functions of the Gaussian process. Ann. Probab. 1 66–103.
Mathematical Reviews (MathSciNet): MR346884
Digital Object Identifier: doi:10.1214/aop/1176997026
[16] Duren, P. and Schuster, A. (2004). Bergman Spaces. Mathematical Surveys and Monographs 100. Amer. Math. Soc., Providence, RI.
Mathematical Reviews (MathSciNet): MR2033762
[17] Gårding, J. (1992). Shape from texture for smooth curved surfaces in perspective projection. J. Math. Imaging Vision 2 327–350.
[18] Gladyshev, E. G. (1961). A new limit theorem for stochastic processes with Gaussian increments. Theory Probab. Appl. 6 52–61.
Mathematical Reviews (MathSciNet): MR145574
[19] Guyon, X. and Leon, G. (1989). Convergence en loi des h-variations d’un processus gaussien stationnaire. Ann. Inst. H. Poincaré 25 265–282.
Mathematical Reviews (MathSciNet): MR1023952
Zentralblatt MATH: 0691.60017
[20] Guyon, X. and Perrin, O. (2000). Identification of space deformation using linear and superficial quadratic variations. Statist. Probab. Lett. 47 307–316.
Mathematical Reviews (MathSciNet): MR1747492
[21] Hanson, D. L. and Wright, F. T. (1971). A bound on tail probabilities for quadratic form in independent random variables. Ann. Math. Statist. 42 1079–1083.
Mathematical Reviews (MathSciNet): MR279864
Zentralblatt MATH: 0216.22203
Digital Object Identifier: doi:10.1214/aoms/1177693335
Project Euclid: euclid.aoms/1177693335
[22] Hu, W. (2001). Dark synergy: Gravitational lensing and the cmb. Phys. Rev. D 65.
[23] Iovleff, S. and Perrin, O. (2004). Estimating a nonstationary spatial structure using simulated annealing. J. Comput. Graph. Statist. 13 90–105.
Mathematical Reviews (MathSciNet): MR2044872
Digital Object Identifier: doi:10.1198/1061860043100
[24] Istas, J. and Lang, G. (1997). Quadratic variations and estimation of the local Hölder index of a Gaussian process. Ann. Inst. H. Poincaré Probab. Statist. 33 407–436.
Mathematical Reviews (MathSciNet): MR1465796
Digital Object Identifier: doi:10.1016/S0246-0203(97)80099-4
[25] Klein, R. and Gine, E. (1975). On quadratic variation of processes with Gaussian increments. Ann. Probab. 3 716–721.
Mathematical Reviews (MathSciNet): MR378070
Digital Object Identifier: doi:10.1214/aop/1176996311
[26] Krushkal’, S. L. (1979). Quasiconformal Mappings and Riemann Surfaces. V. H. Winston & Sons, Washington, DC.
Mathematical Reviews (MathSciNet): MR536488
[27] Ławrynowicz, J. (1983). Quasiconformal Mappings in the Plane: Parametrical Methods. Lecture Notes in Mathematics 978. Springer, Berlin.
Mathematical Reviews (MathSciNet): MR702025
[28] Lehto, O. and Virtanen, K. I. (1965). Quasiconformal Mappings in the Plane. Springer, New York.
Mathematical Reviews (MathSciNet): MR344463
[29] Leon, J. and Ortega, J. (1989). Weak convergence of different types of variation for biparametric Gaussian processes. In Limit Theorems in Probability and Statistics. Colloqnia Mathematica Societatis János Bolyali 57 349–364.
Mathematical Reviews (MathSciNet): MR1116798
[30] Lévy, P. (1940). Le mouvement brownien plan. Amer. J. Math. 62 487–550.
Mathematical Reviews (MathSciNet): MR2734
Digital Object Identifier: doi:10.2307/2371467
[31] Loh, W. (2005). Fixed-domain asymptotics for a subclass of matern-type Gaussian random fields. Ann. Statist. 33 2344–2394.
Mathematical Reviews (MathSciNet): MR2211089
Digital Object Identifier: doi:10.1214/009053605000000516
Project Euclid: euclid.aos/1132936566
[32] Malik, J. and Rosenholtz, R. (1997). Computing local surface orientation and shape from texture for curved surfaces. Int. J. Comp. Vision 23 149–168.
[33] Perrin, O. (1998). Functional convergence in distribution of quadratic variations for a large class of Gaussian processes: Application to a time deformation model. Technical report, Unit of Biometrics at Avignon.
[34] Perrin, O. and Meiring, W. (1999). Identifiability for non-stationary spatial structure. J. Appl. Probab. 36 1244–1250.
Mathematical Reviews (MathSciNet): MR1746409
Zentralblatt MATH: 0993.60047
Digital Object Identifier: doi:10.1239/jap/1032374771
Project Euclid: euclid.jap/1032374771
[35] Perrin, O. and Senoussi, R. (2000). Reducing non-stationary random fields to stationarity and isotropy using a space deformation. Statist. Probab. Lett. 48 23–32.
Mathematical Reviews (MathSciNet): MR1767607
[36] Pommerenke, C. (1975). Univalent Functions. Vandenhoeck & Ruprecht, Göttingen, Germany.
Mathematical Reviews (MathSciNet): MR507768
[37] Sampson, P. and Guttorp, P. (1992). Nonparametric estimation of nonstationary spatial covariance structure. J. Amer. Statist. Assoc. 87 108–119.
[38] Schmidt, A. and O’Hagan, A. (2003). Bayesian inference for nonstationary spatial covariance structure via spatial deformations. J. Roy. Statist. Soc. Ser. B 65 745–758.
Mathematical Reviews (MathSciNet): MR655429
[39] Stein, M. L. (1999). Interpolation of Spatial Data: Some Theory for Kriging. Springer, New York.
Mathematical Reviews (MathSciNet): MR1697409
[40] Stompor, R. and Efstathiou, G. (1999). Gravitational lensing of the cosmic microwave background anisotropies and cosmological parameter estimation. Monthly Notices of the Royal Astronomical Society 302 735–747.
[41] Strait, P. T. (1969). On Berman’s version of the Lévy–Baxter theorem. Proc. Amer. Math. Soc. 23 91–93.
Mathematical Reviews (MathSciNet): MR246358
[42] Zhang, H. (2004). Inconsistent estimation and asymptotically equal interpolations in model-based geostatistics. J. Amer. Statist. Assoc. 99 250–261.
Mathematical Reviews (MathSciNet): MR2054303
Zentralblatt MATH: 1089.62538
Digital Object Identifier: doi:10.1198/016214504000000241

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