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dc.contributor.authorVladik Kreinovichen_US
dc.contributor.authorHung T. Nguyenen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.description.abstract© Springer International Publishing Switzerland 2015. In many practical situations, we need to select one of the two alternatives, and we do not know the exact form of the user’s utility function—e.g., we only know that it is increasing. In this case, stochastic dominance result says that if the cumulative distribution function (cdf) corresponding to the first alternative is always smaller than or equal to the cdf corresponding to the second alternative, then the first alternative is better. This criterion works well in many practical situations, but often, we have situations when for most points, the first cdf is smaller but at some points, the first cdf is larger. In this paper,we showthat in such situations of approximate stochastic dominance, we can also conclude that the first alternative is better—provided that the set of points x at which the first cdf is larger is sufficiently small.en_US
dc.subjectComputer Scienceen_US
dc.titleWhat if we only have approximate stochastic dominance?en_US
dc.typeBook Seriesen_US
article.title.sourcetitleStudies in Computational Intelligenceen_US
article.volume583en_US of Texas at El Pasoen_US Mexico State University Las Crucesen_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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