Dilation and Asymmetric Relevance

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Proceedings of Machine Learning Research 103:324-26 (2019)
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Abstract

A characterization result of dilation in terms of positive and negative association admits an extremal counterexample, which we present together with a minor repair of the result. Dilation may be asymmetric whereas covariation itself is symmetric. Dilation is still characterized in terms of positive and negative covariation, however, once the event to be dilated has been specified.

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Author Profiles

Arthur Paul Pedersen
Gregory Wheeler
Frankfurt School Of Finance And Management

Citations of this work

Moving Beyond Sets of Probabilities.Gregory Wheeler - 2021 - Statistical Science 36 (2):201--204.

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References found in this work

The Extent of Dilation of Sets of Probabilities and the Asymptotics of Robust Bayesian Inference.Timothy Herron, Teddy Seidenfeld & Larry Wasserman - 1994 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1994:250 - 259.

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