Abstract
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.
Citation
Samuel N. Cohen. "Data-driven nonlinear expectations for statistical uncertainty in decisions." Electron. J. Statist. 11 (1) 1858 - 1889, 2017. https://doi.org/10.1214/17-EJS1278
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