The following anticoncentration property is proved. The probability that the $k$-order statistic of an arbitrarily correlated jointly Gaussian random vector $X$ with unit variance components lies within an interval of length $\varepsilon$ is bounded above by $2{\varepsilon}k ({ 1+\mathrm{E}[\|X\|_\infty ]}) $. This bound has implications for generalized error rate control in statistical high-dimensional multiple hypothesis testing problems, which are discussed subsequently.

翻译：以下反浓缩特性得到证明。 任意关联的高斯任意随机矢量和单位差异成分的按顺序排列的美元统计数据在长度间隔内(瓦列普西隆元)的概率为2美元以上(瓦列普西隆元)k ({# mathr{E}{{ ⁇ X ⁇ infty}}) 美元。这一约束对统计高维多重假设测试问题中普遍误差率控制产生影响,下文将讨论这些问题。