18,843 research outputs found

    Edgeworth Expansion by Stein's Method

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    Edgeworth expansion provides higher-order corrections to the normal approximation for a probability distribution. The classical proof of Edgeworth expansion is via characteristic functions. As a powerful method for distributional approximations, Stein's method has also been used to prove Edgeworth expansion results. However, these results assume that either the test function is smooth (which excludes indicator functions of the half line) or that the random variables are continuous (which excludes random variables having only a continuous component). Thus, how to recover the classical Edgeworth expansion result using Stein's method has remained an open problem. In this paper, we develop Stein's method for two-term Edgeworth expansions in a general case. Our approach involves repeated use of Stein equations, Stein identities via Stein kernels, and a replacement argument.Comment: 22 page

    On the Approximate Core and Nucleon of Flow Games

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    The flow game with public arcs is a cooperative revenue game derived from a flow network. In this game, each player possesses an arc, while certain arcs, known as public arcs, are not owned by any specific player and are accessible to any coalition. The aim of this game is to maximize the flow that can be routed in the network through strategic coalition formation. By exploring its connection to the maximum partially disjoint path problem, we investigate the approximate core and nucleon of the flow game with public arcs. The approximate core is an extension of the core that allows for some deviation in group rationality, while the nucleon is a multiplicative analogue of the nucleolus. In this paper, we provide two complete characterizations for the optimal approximate core and show that the nucleon can be computed in polynomial time
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