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Capacities, Measurable Selection and Dynamic Programming Part I: Abstract Framework

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abstract

We give a brief presentation of the capacity theory and show how it derives naturally a measurable selection theorem following the approach of Dellacherie (1972). Then we present the classical method to prove the dynamic programming of discrete time stochastic control problem, using measurable selection arguments. At last, we propose a continuous time extension, that is an abstract framework for the continuous time dynamic programming principle (DPP).

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math.ST 1

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2024 1

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UNVERDICTED 1

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On the optimality of coin-betting for mean estimation

math.ST · 2024-12-03 · unverdicted · novelty 7.0

Coin-betting is optimal among e-variable frameworks for mean testing of bounded variables, yielding an explicit characterization of all admissible e-variables and e-processes.

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  • On the optimality of coin-betting for mean estimation math.ST · 2024-12-03 · unverdicted · none · ref 6 · internal anchor

    Coin-betting is optimal among e-variable frameworks for mean testing of bounded variables, yielding an explicit characterization of all admissible e-variables and e-processes.