On uniform laws of large numbers for smoothed empirical measures

被引：0
|
作者：
Gaenssler, P [1 ]
Rost, D [1 ]
机构：
[1] Univ Munich, Inst Math, D-80333 Munich, Germany
来源：
HIGH DIMENSIONAL PROBABILITY II | 2000年 / 47卷
关键词：
D O I：
暂无
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
We consider function-indexed smoothed empirical measures on linear metric spaces and focus on uniform laws of large numbers (ULLN) comparable with Glivenko-Cantelli results in the non-smoothed case. Using the random measure process approach we are able to give a set of sufficient conditions for a ULLN which are different from the ones known in the literature and are more close to being necessary.
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页码：79 / 87
页数：9
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