In this paper, we derive a new version of Hanson-Wright inequality for a sparse bilinear form of sub-Gaussian variables. Our results are generalization of previous deviation inequalities that consider either sparse quadratic forms or dense bilinear forms. We apply the new concentration inequality to testing the cross-covariance matrix when data are subject to missing. Using our results, we can find a threshold value of correlations that controls the family-wise error rate. Furthermore, we discuss the multiplicative measurement error case for the bilinear form with a boundedness condition.
翻译:在本文中,我们得出了汉森-怀特不平等的新版本,用于一种稀薄的双线型亚加苏西变量。 我们的结果是概括以往的偏差不平等,这种偏差既考虑稀疏的二次形式,也考虑密集的双线形式。 当数据丢失时,我们应用新的集中不平等来测试交叉变量矩阵。 使用我们的结果, 我们可以找到控制家庭误差率的关联值的临界值。 此外, 我们讨论双线型双线式的多倍性测量错误, 并且有约束性条件 。