Factorable
发表于 2025-3-28 18:31:28
https://doi.org/10.1007/978-3-319-71538-4a where exports of coffee to European Union are analyzed to identify outliers that might be linked to potential frauds. An additional short simulation is presented to strengthen the usefulness of the proposed method.
宪法没有
发表于 2025-3-28 22:34:32
Vania Smith-Oka Ph.D.,Maryam Rokhideh M.A.d with the case where we imprecisely know the probability that two elements should belong to the same partition, and where we want to search the set of most probable partitions. We study the corresponding algorithmic problem on graphs, showing that it is difficult, and propose heuristic procedures that we test on data sets.
barium-study
发表于 2025-3-29 02:33:28
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LINE
发表于 2025-3-29 03:17:38
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Blasphemy
发表于 2025-3-29 10:57:10
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magnanimity
发表于 2025-3-29 11:41:06
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ICLE
发表于 2025-3-29 16:28:52
,K-Partitioning with Imprecise Probabilistic Edges,d with the case where we imprecisely know the probability that two elements should belong to the same partition, and where we want to search the set of most probable partitions. We study the corresponding algorithmic problem on graphs, showing that it is difficult, and propose heuristic procedures that we test on data sets.
BURSA
发表于 2025-3-29 22:37:37
,Copula-Based Divergence Measures for Dependence Between Random Vectors,ide an extended axiomatic framework for the general setting of . random vectors. The univariate marginal distributions are assumed to be continuous, allowing copula theory to come into play and as such guarantee margin-freeness. Using basic measure theory, our definition is also applicable to copulas having a singular component.
牵连
发表于 2025-3-30 03:56:54
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控诉
发表于 2025-3-30 07:33:02
,Multi-dimensional Maximal Coherent Subsets Made Easy: Illustration on an Estimation Problem,es of information are multi-dimensional sets or polytopes. While the problem remains difficult for general polytopes, we show that it can be solved more efficiently for hyperrectangles. We then illustrate how such an approach could be used to estimate linear models in the presence of outliers or in the presence of misspecified model.