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Title of article :
Computing functional estimators of spatiotemporal long-range dependence parameters in the spectral-wavelet domain
Author/Authors :
Frيas، نويسنده , , M.P. and Ruiz-Medina، نويسنده , , M.D.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2011
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Abstract :
This paper addresses the problem of parameter estimation of spatiotemporal long-range dependence models from functional spectral data. Four wavelet-based functional estimation algorithms are proposed to approximate the multidimensional strong-dependence parameter, characterizing the covariance tail behavior of the spatiotemporal non-self-similar model class studied in Frيas et al. (2006b, 2009). Wavelet regression is performed in all of them. Functional spectral data are averaged in the first and fourth algorithms, while, in the second and third ones, averaging is performed on the wavelet regression estimates. Smoothing over the wavelet translation parameter is performed, within each resolution level, only in Algorithms 3 and 4. A simulation study is carried out to illustrate the performance of the four functional estimation algorithms proposed under different scenarios.
Keywords :
Spectral functional data , wavelet transform , Long-range dependence parameters , Spatiotemporal parametric models
Journal title :
Journal of Statistical Planning and Inference
Journal title :
Journal of Statistical Planning and Inference
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