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Spatiotemporal generation of long‐range dependence models and estimation
Author(s) -
Frías M. P.,
RuizMedina M. D.,
Alonso F. J.,
Angulo J. M.
Publication year - 2006
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.756
Subject(s) - separable space , range (aeronautics) , parametric statistics , mathematics , isotropy , variogram , statistical physics , econometrics , computer science , mathematical optimization , algorithm , mathematical analysis , statistics , kriging , physics , optics , materials science , composite material
A parametric family of spatiotemporal models displaying separable isotropic long‐range dependence, in space and time, is introduced in a fractional generalized framework. The weak‐sense implementation of estimation methods based on the integrated periodogram, the variogram and the wavelet transform, to estimate the long‐memory parameter vector is discussed. The construction of separable and non‐separable anisotropic long‐range dependence spatiotemporal processes is also described considering fractional integration filters. Copyright © 2005 John Wiley & Sons, Ltd.