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The repeated insertion model for rankings: Missing link between two subset choice models

机译:排名的重复插入模型:两个子集选择模型之间的链接缺失

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Several probabilistic models for subset choice have been proposed in the literature, for example, to explain approval voting data. We show that Marley et al.'s latent scale model is subsumed by Falmagne and Regenwetter's size-independent model, in the sense that every choice probability distribution generated by the former can also be explained by the latter. Our proof relies on the construction of a probabilistic ranking model which we label the "repeated insertion model." This model is a special case of Marden's orthogonal contrast model class and, in turn, includes the classical Mallows phi-model as a special case. We explore its basic properties as well as its relationship to Fligner and Verducci's multistage ranking model.
机译:文献中已经提出了几种用于子集选择的概率模型,例如,以解释批准投票数据。我们表明,在某种意义上,前者所产生的每个选择概率分布也可以由后者来解释,从这个意义上说,Marley等人的潜在规模模型被Falmagne和Regenwetter的大小无关模型所包含。我们的证明依赖于概率排序模型的构建,我们将其标记为“重复插入模型”。该模型是Marden正交对比模型类的特例,而特例包括经典的Mallows phi模型。我们将探讨其基本属性以及与Fligner和Verducci多阶段排名模型的关系。

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