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About: Vuong's closeness test     Goto   Sponge   NotDistinct   Permalink

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Type: yago:WikicatStatisticalTestsyago:Abstraction100002137yago:Cognition100023271yago:Experiment105798043yago:HigherCognitiveProcess105770664yago:Inquiry105797597yago:ProblemSolving105796750yago:Process105701363yago:PsychologicalFeature100023100yago:Thinking105770926yago:Trial105799212 New Facet based on Instances of this Class

In statistics, the Vuong closeness test is a likelihood-ratio-based test for model selection using the Kullback–Leibler information criterion. This statistic makes probabilistic statements about two models. They can be nested, strictly non-nested or partially non-nested (also called overlapping). The statistic tests the null hypothesis that the two models are equally close to the true data generating process, against the alternative that one model is closer. It cannot make any decision whether the "closer" model is the true model.