On least squares estimation for long-memory lattice processes

Publikationstyp: Zeitschriftenartikel
Autor/innen: Beran, Jan; Ghosh, Sucharita; Schell, Dieter
Erscheinungsjahr: 2009
Erschienen in: Journal of Multivariate Analysis ; 100 (2009), 10. - S. 2178-2194
DOI (zitierfähiger Link): https://dx.doi.org/10.1016/j.jmva.2009.04.007
Zusammenfassung:
A flexible class of anisotropic stationary lattice processes with long memory can be defined in terms of a two-way fractional ARIMA (FARIMA) representation. We consider parameter estimation based on minimizing an approximate residual sum of squares. The method can be applied to sampling areas that are not necessarily rectangular. A central limit theorem is derived under general conditions. The method is illustrated by an analysis of satellite data consisting of total column ozone amounts in Europe and the Atlantic respectively.
Fachgebiet (DDC): 310 Statistik
Schlagwörter: Long memory, Fractional ARIMA process, Lattice process, Maximum likelihood estimation, Anisotropy
Universitätsbibliographie: Ja

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BERAN, Jan, Sucharita GHOSH, Dieter SCHELL, 2009. On least squares estimation for long-memory lattice processes. In: Journal of Multivariate Analysis. 100(10), pp. 2178-2194. Available under: doi: 10.1016/j.jmva.2009.04.007

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