Local Whittle estimator for anisotropic random fields

A local Whittle estimator is developed to simultaneously estimate the long memory parameters for stationary anisotropic scalar random fields. It is shown that these estimators are consistent and asymptotically normal, under some weak technical conditions. A brief simulation study illustrates a practical application of the estimator.

[1]  D. Brillinger Time series - data analysis and theory , 1981, Classics in applied mathematics.

[2]  Mark M. Meerschaert,et al.  Operator scaling stable random fields , 2006 .

[3]  M. Taqqu,et al.  Large-Sample Properties of Parameter Estimates for Strongly Dependent Stationary Gaussian Time Series , 1986 .

[4]  P. Heywood Trigonometric Series , 1968, Nature.

[5]  E. Hannan The asymptotic theory of linear time-series models , 1973, Journal of Applied Probability.

[6]  David R. Brillinger,et al.  Time Series: Data Analysis and Theory. , 1982 .

[7]  P. Robinson Long memory time series , 2003 .

[8]  Noel A Cressie,et al.  Statistics for Spatial Data. , 1992 .

[9]  D. Surgailis,et al.  A central limit theorem for quadratic forms in strongly dependent linear variables and its application to asymptotical normality of Whittle's estimate , 1990 .

[10]  Susan A. Murphy,et al.  Monographs on statistics and applied probability , 1990 .

[11]  B. B. Bhattacharyya,et al.  Parameter estimates for fractional autoregressive spatial processes , 2005, math/0501423.

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

[13]  P. Robinson Gaussian Semiparametric Estimation of Long Range Dependence , 1995 .

[14]  Nikolai N. Leonenko,et al.  On the Whittle estimators for some classes of continuous-parameter random processes and fields , 2006 .

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

[16]  G. Katul,et al.  Soil moisture and vegetation controls on evapotranspiration in a heterogeneous Mediterranean ecosystem on Sardinia, Italy , 2006 .

[17]  D. Applebaum Stable non-Gaussian random processes , 1995, The Mathematical Gazette.

[18]  George Labahn,et al.  Inversion of Toeplitz Matrices with Only Two Standard Equations , 1992 .

[19]  Richard A. Davis,et al.  Time Series: Theory and Methods , 2013 .

[20]  X. Guyon Parameter estimation for a stationary process on a d-dimensional lattice , 1982 .

[21]  Harold Auradou,et al.  Anisotropic self-affine properties of experimental fracture surfaces , 2006 .

[22]  Carlos Velasco Gómez Gaussian semiparametric estimation of non-stationary time series , 1998 .

[23]  S. N. Lahiri,et al.  A necessary and sufficient condition for asymptotic independence of discrete Fourier transforms under short- and long-range dependence , 2003 .

[24]  Harold Widom,et al.  Inversion of Toeplitz matrices II , 1959 .

[25]  Murray Rosenblatt,et al.  Gaussian and Non-Gaussian Linear Time Series and Random Fields , 1999 .

[26]  P. Robinson,et al.  Rates of convergence and optimal spectral bandwidth for long range dependence , 1994 .

[27]  Jan Beran,et al.  Statistics for long-memory processes , 1994 .

[28]  F. Lavancier,et al.  Long memory random fields , 2006 .

[29]  David A. Benson,et al.  Aquifer operator scaling and the effect on solute mixing and dispersion , 2006 .

[30]  Anne Estrade,et al.  Anisotropic Analysis of Some Gaussian Models , 2003 .

[31]  Rainer Dahlhaus Asymptotic normality of spectral estimates , 1985 .

[32]  Murad S. Taqqu,et al.  Robustness of whittle-type estimators for time series with long-range dependence , 1997 .

[33]  U. Grenander,et al.  Toeplitz Forms And Their Applications , 1958 .

[34]  P. Hall,et al.  Martingale Limit Theory and its Application. , 1984 .

[35]  P. Robinson Log-Periodogram Regression of Time Series with Long Range Dependence , 1995 .