Multivariate Almost Stochastic Dominance: Transfer Characterizations and Sufficient Conditions Under Dependence Uncertainty
针对多目标不确定性决策，基于属性边际分布或均值和方差，给出了多元几乎随机占优的充分条件，为复杂环境下的重要决策提供实用工具。
Decision with Several Objectives Under Uncertainty Important decisions typically involve multiple objectives and uncertainty. Assessing both multivariate utility and multivariate distributions for the attributes can be challenging. Moreover, big decisions are usually made by boards or committees with members holding divergent views and preferences and facing pressures from different stakeholders. Thus, a full-blown traditional decision analysis that leads to the computation of expected utility is very difficult at best and often not possible. In “Multivariate Almost Stochastic Dominance: Transfer Characterizations and Sufficient Conditions Under Dependence Uncertainty” Müller, Scarsini, Tsetlin, and Winkler develop sufficient conditions for multivariate almost stochastic dominance based on marginal distributions of the attributes or just on their means and variances. Such tools, consistent with normative decision analysis, are useful when making important decisions in today’s fast-moving and often complex world.