Upper functions for Lp-norms of Gaussian random fields

被引:1
|
作者
Lepski, Oleg [1 ]
机构
[1] Aix Marseille Univ, Inst Math Marseille, 39 Rue F Joliot Curie, F-13453 Marseille, France
关键词
Dudley's integral; Gaussian random field; metric entropy; upper function; EMPIRICAL PROCESSES THEORY; CONCENTRATION INEQUALITIES; ADAPTIVE ESTIMATION; DENSITY-ESTIMATION; II; APPLICATION; BOUNDS; SELECTION;
D O I
10.3150/14-BEJ674
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
In this paper, we are interested in finding upper functions for a collection of random variables {parallel to xi(-)(h)parallel to(p), (h) over right arrow is an element of H), 1 <= p < infinity. Here xi(<(h)over right arrow>) (x), x is an element of (-b, b)(d), d >= 1 is a kernel -type Gaussian random field and parallel to.parallel to(p) stands for L-p-norm on (-b, b)(d). The set H consists of d-variate vector -functions defined on (-b, b)(d) and taking values in some countable net in R-+(d) . We seek a non-random family {Psi(epsilon) ((h) over right arrow), (h) over right arrow is an element of H} such that E{sup((h) over right arrow is an element of H)[parallel to xi((h) over right arrow)parallel to(p) - Psi(epsilon) ((h) over right arrow)](+)}(q) <= epsilon(q), q >= 1where epsilon > 0 is prescribed level.
引用
收藏
页码:732 / 773
页数:42
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