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- W2034881601 abstract "A law of large numbers for the maximum of i.i.d. univariate normal random variables is extended to a general multivariate case. Let $mathbf{Z}_i$ denote i.i.d. Banach space valued random variables with a centered Gaussian distribution. Let $mathbf{K}$ denote the unit ball of the reproducing kernel Hilbert space. Then with probability 1, the maximum distance from the sample points $mathbf{Z}_1, mathbf{Z}_2,ldots, mathbf{Z}_n$ to the set $sqrt{2 log n} mathbf{K}$ approaches zero. In addition, the sample forms epsilon nets for this set as $n$ tends to infinity." @default.
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- W2034881601 date "1988-07-01" @default.
- W2034881601 modified "2023-10-14" @default.
- W2034881601 title "Characteristics of Normal Samples" @default.
- W2034881601 doi "https://doi.org/10.1214/aop/1176991690" @default.
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