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A multivariate Berry-Esseen theorem with explicit constants

机译:具有明确常量的多变量莓果贝瑞定理

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摘要

We provide a Lyapunov type bound in the multivariate central limit theorem for sums of independent, but not necessarily identically distributed random vectors. The error in the normal approximation is estimated for certain classes of sets, which include the class of measurable convex sets. The error bound is stated with explicit constants. The result is proved by means of Stein's method. In addition, we improve the constant in the bound of the Gaussian perimeter of convex sets.
机译:我们在多元中心极限定理中为独立但不一定相同分布的随机向量和提供了一个Lyapunov型界。对于某些集合类,包括可测凸集类,正态近似中的误差是估计的。错误界限用显式常量表示。用Stein方法证明了这一结果。此外,我们还改进了凸集高斯周长界的常数。

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