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Titlebook: COMPSTAT 2008; Proceedings in Compu Paula Brito Conference proceedings 2008 Physica-Verlag Heidelberg 2008 ANOVA.Fitting.Graph.Latent varia

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樓主: palliative
41#
發(fā)表于 2025-3-28 15:23:02 | 只看該作者
Overview: Includes supplementary material: 978-3-7908-2083-6978-3-7908-2084-3
42#
發(fā)表于 2025-3-28 20:41:06 | 只看該作者
Fundamental, or Structural, Disequilibriaitly parallelizing basic R operations, such as vectorized arithmetic operations; this is suitable for taking advantage of multi-core processors with shared memory. The second approach is based on developing a small set of explicit parallel computation directives and is most useful in a distributed memory framework.
43#
發(fā)表于 2025-3-28 23:14:18 | 只看該作者
Paula BritoIncludes supplementary material:
44#
發(fā)表于 2025-3-29 06:02:43 | 只看該作者
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45#
發(fā)表于 2025-3-29 10:58:57 | 只看該作者
46#
發(fā)表于 2025-3-29 11:36:52 | 只看該作者
47#
發(fā)表于 2025-3-29 17:09:24 | 只看該作者
Computable Statistical Research and Practicecrudely described by 3 stages: scoping, to assess what can and needs to be done; analysis, where this is accomplished; and reporting, which communicates the results to others. Barriers to the reuse of computations can be found in the translational needs driving the transition between sub-activities;
48#
發(fā)表于 2025-3-29 23:18:25 | 只看該作者
Implicit and Explicit Parallel Computing in Ritly parallelizing basic R operations, such as vectorized arithmetic operations; this is suitable for taking advantage of multi-core processors with shared memory. The second approach is based on developing a small set of explicit parallel computation directives and is most useful in a distributed m
49#
發(fā)表于 2025-3-30 03:15:03 | 只看該作者
Probabilistic Modeling for Symbolic Data provides exploratory methods for revealing the structure of such data and proceeds typically by heuristical, even if suggestive methods that generalize criteria and algorithms from classical multivariate statistics. In contrast, this paper proposes to base the analysis of symbolic data on probabili
50#
發(fā)表于 2025-3-30 04:34:48 | 只看該作者
Monothetic Divisive Clustering with Geographical Constraintse read as a decision tree. We propose in this paper a new version of this method called C-DIVCLUS-T which is able to take contiguity constraints into account. We apply C-DIVCLUS-T to hydrological areas described by agricultural and environmental variables, in order to take their geographical contigu
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