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Titlebook: Geostatistics for Compositional Data with R; Raimon Tolosana-Delgado,Ute Mueller Book 2021 Springer Nature Switzerland AG 2021 composition

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發(fā)表于 2025-3-25 03:22:33 | 只看該作者
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發(fā)表于 2025-3-25 08:42:29 | 只看該作者
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發(fā)表于 2025-3-25 14:06:14 | 只看該作者
Leadership, Vision and Strategy,mation, then testing the transformed data for multivariate normality, applying an affine equivariant multivariate normal score transformation, if necessary, modelling the spatial continuity of the normal scores, followed by simulation and back-transformation. Several algorithms are available for sim
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發(fā)表于 2025-3-25 18:48:09 | 只看該作者
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發(fā)表于 2025-3-25 22:07:02 | 只看該作者
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發(fā)表于 2025-3-26 05:43:49 | 只看該作者
Book 2021r concentrations distributed in space which exhibit spatial correlation. The book can be divided into four blocks. The first block sets the framework and provides some background on compositional data analysis. Block two introduces compositional exploratory tools for both non-spatial and spatial asp
28#
發(fā)表于 2025-3-26 10:47:28 | 只看該作者
29#
發(fā)表于 2025-3-26 14:49:56 | 只看該作者
Gabriel Tortella,Gloria Quiroga, the multivariate normal score transformation needs to be affine equivariant. In this chapter we introduce one such transformation, namely the Gaussian flow anamorphosis and briefly describe its properties.
30#
發(fā)表于 2025-3-26 18:42:57 | 只看該作者
Leadership, Vision and Strategy,ssary, modelling the spatial continuity of the normal scores, followed by simulation and back-transformation. Several algorithms are available for simulating Gaussian random functions. These include LU decomposition simulation, sequential Gaussian simulation and turning bands simulation, which will be introduced briefly.
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