On least squares estimation for long-memory lattice processes
On least squares estimation for long-memory lattice processes
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DOI：
10.1016/j.jmva.2009.04.007
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发表时间：
2009-11
期刊：
影响因子：
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通讯作者：
J. Beran;Sucharita Ghosh;Dieter Schell
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文献类型：
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作者：
J. Beran;Sucharita Ghosh;Dieter Schell
一类具有长记忆的柔性各向异性平稳晶格过程可以用双向分数ARIMA （FARIMA）表示来定义。我们考虑基于最小化近似残差平方和的参数估计。该方法可以应用于不一定是矩形的采样区域。在一般条件下，导出了一个中心极限定理。对欧洲和大西洋的臭氧柱总量卫星数据的分析说明了这种方法。
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.