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Efficiency of nonparametric e-tests
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The notion of an e-value has been recently proposed as a possible alternative to critical regions and p-values in statistical hypothesis testing. In this paper we consider testing the nonparametric hypothesis of symmetry, introduce analogues for e-values of three popular nonparametric tests, define an analogue for e-values of Pitman's asymptotic relative efficiency, and apply it to the three nonparametric tests. We discuss limitations of our simple definition of asymptotic relative efficiency and list directions of further research.
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Testing maximum entropy models with e-values
It derives an exact growth-rate optimal e-variable for microcanonical maximum entropy tests and shows this e-variable is a valid, near-optimal approximation for canonical tests.
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