Locally Homogeneous and Isotropic Gaussian Fields in Kriging

The paper deals with the application of the theory of locally homogeneous and isotropic Gaussian fields (LHIGF) to probabilistic modelling of multivariate data structures. An asymptotic model is also studied, when the correlation function parameter of the Gaussian field tends to infinity. The kriging procedure is developed which presents a simple extrapolator by means of a matrix of degrees of the distances between pairs of the points of measurement. The resulting model is rather simple and can be defined only by the mean and variance parameters, efficiently evaluated by maximal likelihood method. The results of application of the extrapolation method developed for two analytically computed surfaces and estimation of the position of the spacecraft re-entering the atmosphere are given.

[1]  Jonas Mockus Bayesian Heuristic Approach to Discrete and Global Optimization: Algorithms, Visualization, Software, and Applications , 1996 .

[2]  M. Levenson,et al.  Realistic Estimates of the Consequences of Nuclear Accidents , 1981 .

[3]  Francis Tuerlinckx,et al.  Maximum likelihood estimation in processes of Ornstein-Uhlenbeck type , 2009 .

[4]  A. Bogush,et al.  Gaussian field expansions for large aperture antennas , 1986 .

[5]  D. Shepard A two-dimensional interpolation function for irregularly-spaced data , 1968, ACM National Conference.

[6]  Donald R. Jones,et al.  A Taxonomy of Global Optimization Methods Based on Response Surfaces , 2001, J. Glob. Optim..

[7]  Thomas H. Jordan,et al.  Stochastic Modeling of Seafloor Morphology: Inversion of Sea Beam Data for Second-Order Statistics , 1988 .

[8]  R. Adler The Geometry of Random Fields , 2009 .

[9]  R. Adler,et al.  The Geometry of Random Fields , 1982 .

[10]  J. Gower Euclidean Distance Geometry , 1982 .

[11]  Zhiyi Chi,et al.  Approximating likelihoods for large spatial data sets , 2004 .

[12]  Fernando Lopez-Caballero,et al.  Assessment of variability and uncertainties effects on the seismic response of a liquefiable soil profile , 2010 .

[13]  G. Matheron Principles of geostatistics , 1963 .

[14]  J. L. Maryak,et al.  Bayesian Heuristic Approach to Discrete and Global Optimization , 1999, Technometrics.

[15]  Gillespie,et al.  Exact numerical simulation of the Ornstein-Uhlenbeck process and its integral. , 1996, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[16]  Mudry,et al.  Localization in Two Dimensions, Gaussian Field Theories, and Multifractality. , 1996, Physical review letters.

[17]  V. M. Alipchenkov,et al.  Modelling of transport and dispersion of arbitrary-density particles in turbulent flows , 2010 .

[18]  D. Zwart,et al.  Extrapolation Practice for Ecotoxicological Effect Characterization of Chemicals , 2008 .

[19]  John A. Goff,et al.  Modal fields: A new method for characterization of random seismic velocity heterogeneity , 1994 .

[20]  L. Schumaker Fitting surfaces to scattered data , 1976 .

[21]  S. C. Lim,et al.  Generalized Whittle–Matérn random field as a model of correlated fluctuations , 2009, 0901.3581.

[22]  J. Mockus,et al.  The Bayesian approach to global optimization , 1989 .

[23]  Antanas Zilinskas,et al.  Axiomatic approach to statistical models and their use in multimodal optimization theory , 1982, Math. Program..

[24]  Statistical Inferences for Termination of Markov Type Random Search Algorithms , 2009 .

[25]  Roger Woodard,et al.  Interpolation of Spatial Data: Some Theory for Kriging , 1999, Technometrics.

[26]  Charles R. Johnson,et al.  Topics in Matrix Analysis , 1991 .