On least squares estimation for long-memory lattice processes

Jan Beran, Sucharita Ghosh and Dieter Schell

Journal of Multivariate Analysis, 2009, vol. 100, issue 10, 2178-2194

Abstract: 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.

Keywords: Long; memory; Fractional; ARIMA; process; Lattice; process; Maximum; likelihood; estimation; Anisotropy (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (7)

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