Fractional Gaussian fields provide a rich class of spatial models and have a long history of applications in multiple branches of science. However, estimation and inference for fractional Gaussian fields present significant challenges. This book chapter investigates the use of the fractional Laplacian differencing on regular lattices to approximate to continuum fractional Gaussian fields. Emphasis is given on model based geostatistics and likelihood based computations. For a certain range of the fractional parameter, we demonstrate that there is considerable agreement between the continuum models and their lattice approximations. For that range, the parameter estimates and inferences about the continuum fractional Gaussian fields can be derived from the lattice approximations. Interestingly, regular lattice approximations facilitate fast matrix-free computations and enable anisotropic representations. We illustrate the usefulness of lattice approximations via simulation studies and by analyzing sea surface temperature on the Indian Ocean.
翻译:Fractional Gaussian 字段提供了丰富的空间模型,并具有在多个科学分支中应用的悠久历史。 但是,对分数高斯字段的估计和推断提出了重大挑战。 本书章调查了对普通平面的分数拉普拉西亚差异值的使用,以近似于分数高斯字段的连续性。 重点是基于模型的地理统计学和基于概率的计算。 对于部分参数的某些范围,我们证明在连续模型和其阵列近似值之间有着相当的一致。 对于这一范围,关于连续数高斯字段的参数估计和推论可以从拉蒂斯近值中得出。 有趣的是, 常规拉蒂斯近值有助于快速的无矩阵计算, 并能够进行厌食现象的表达。 我们通过模拟研究和分析印度洋的海面温度来说明拉蒂斯近值的效用。