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sums hit rectangles and sparsely convex sets. Specifically, we derive Gaussian and bootstrap approximations for the … all rectangles, or more generally, sparsely convex sets, and does not require any restrictions on the correlation among … functions depend nontrivially only on a small subset of their arguments, with rectangles being a special case. …
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We derive a central limit theorem for the maximum of a sum of high dimensional random vectors. More precisely, we establish condi- tions under which the distribution of the maximum is approximated by the maximum of a sum of the Gaussian random vectors with the same covariance matrices as the...
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high-dimensional centered random vectors X1, . . . , Xn over the class of rectangles in the case when the covariance matrix …
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