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On least squares estimation for long-memory lattice processes

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2009

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Ghosh, Sucharita

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http://nbn-resolving.de/urn:nbn:de:bsz:352-opus-102279
DOI (zitierfähiger Link)
https://doi.org/10.1016/j.jmva.2009.04.007
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Journal of Multivariate Analysis. 2009, 100(10), pp. 2178-2194. Available under: doi: 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.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
310 Statistik

Schlagwörter

Long memory, Fractional ARIMA process, Lattice process, Maximum likelihood estimation, Anisotropy

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ISO 690BERAN, Jan, Sucharita GHOSH, Dieter SCHELL, 2009. On least squares estimation for long-memory lattice processes. In: Journal of Multivariate Analysis. 2009, 100(10), pp. 2178-2194. Available under: doi: 10.1016/j.jmva.2009.04.007
BibTex
@article{Beran2009least-813,
  year={2009},
  doi={10.1016/j.jmva.2009.04.007},
  title={On least squares estimation for long-memory lattice processes},
  number={10},
  volume={100},
  journal={Journal of Multivariate Analysis},
  pages={2178--2194},
  author={Beran, Jan and Ghosh, Sucharita and Schell, Dieter}
}
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