Neighbourhoods of precise probabilities are instrumental to perform robustness analysis, as they rely on very few parameters. In the first part of this study, we introduced a general, unified view encompassing such neighbourhoods, and revisited some well-known models (pari mutuel, linear vacuous, constant odds-ratio). In this second part, we study models that have received little to no attention, but are induced by classical distances between probabilities, such as the total variation, the Kolmogorov and the distances. We finish by comparing those models in terms of a number of properties: precision, number of extreme points, n-monotonicity, …thus providing possible guidelines to select a neighbourhood rather than another.

中文翻译：

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统一邻域和失真模型：第二部分——新模型和综合

精确概率的邻域有助于执行稳健性分析，因为它们依赖于很少的参数。在本研究的第一部分，我们介绍了包含此类社区的通用统一视图，并重新审视了一些众所周知的模型（彩池、线性真空、恒定赔率比）。在第二部分中，我们研究几乎没有受到关注，但由概率之间的经典距离（例如总变异、Kolmogorov 和距离）引起的模型。我们通过在许多属性方面比较这些模型来结束：精度、极值点的数量、n 单调性……从而为选择一个邻域而不是另一个邻域提供可能的指导方针。