Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models
高维线性模型中低维参数的置信区间
Summary The purpose of this paper is to propose methodologies for statistical inference of low dimensional parameters with high dimensional data. We focus on constructing confidence intervals for individual coefficients and linear combinations of several of them in a linear regression model, although our ideas are applicable in a much broader context. The theoretical results that are presented provide sufficient conditions for the asymptotic normality of the proposed…