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Data-driven nonlinear expectations for statistical uncertainty in decisions. (arXiv:1609.06545v1 [math.ST])

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In stochastic decision problems, one often wants to estimate the underlying probability measure statistically, and then to use this estimate as a basis for decisions. We shall consider how the uncertainty in this estimation can be explicitly and consistently incorporated in the valuation of decisions, using the theory of nonlinear expectations.


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