Open Access
2017 Data-driven nonlinear expectations for statistical uncertainty in decisions
Samuel N. Cohen
Electron. J. Statist. 11(1): 1858-1889 (2017). DOI: 10.1214/17-EJS1278


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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Samuel N. Cohen. "Data-driven nonlinear expectations for statistical uncertainty in decisions." Electron. J. Statist. 11 (1) 1858 - 1889, 2017.


Received: 1 September 2016; Published: 2017
First available in Project Euclid: 28 April 2017

zbMATH: 1362.62063
MathSciNet: MR3641848
Digital Object Identifier: 10.1214/17-EJS1278

Primary: 62F25 , 62F86
Secondary: 62A86 , 90B50 , 91G70

Keywords: nonlinear expectation , robustness , statistical uncertainty

Vol.11 • No. 1 • 2017
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