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A stochastic independence approach for different measures of concentration and specialization

机译:不同集中度和专业化程度的随机独立方法

摘要

From data in the form of a two-way contingency table “Regions × Sectors”, the concepts of specialization and concentration, built from the analysis of conditional distributions or profiles, is based on discrepancies among distributions: between profiles and a uniform distribution for absolute concepts; between profiles and the corresponding marginal distribution for the relative concepts; or between the joint distribution and the product of the marginal distributions for the global concept. This paper provides an extensive numerical analysis of measures derived from this approach and from other approaches used in the literature and shows that while the different measures under consideration display rather similar numerical behaviours, differences of ranking call for a particular care when interpreting the numerical results.
机译:从双向列联表“ Regions×Sectors”的数据中,通过分析条件分布或分布图建立的专业化和集中化概念基于分布之间的差异:分布图和绝对值的均匀分布之间概念;在轮廓和相对概念的相应边际分布之间;或全局概念的联合分布与边际分布的乘积之间。本文对从这种方法和文献中使用的其他方法得出的度量进行了广泛的数值分析,结果表明,虽然所考虑的不同度量显示出相当相似的数值行为,但在解释数值结果时,排名的差异需要特别注意。

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