论文标题
浆果 - 埃斯尼（Berry-Esseen）的投影参数和尺寸增加的部分相关性
Berry-Esseen Bounds for Projection Parameters and Partial Correlations with Increasing Dimension
论文作者
论文摘要
我们提供有限的样本边界，以与基于三明治的标准误差标准化的投影参数的最小二乘估计量的法线近似。我们的结果在增加的尺寸设置以及对数据生成分布的最小假设下。特别是，我们不假定线性回归函数，只需要有限的响应和协变量有限的矩。此外，我们以高矩形的形式为投影参数构建置信集，并在其覆盖范围和准确性上建立有限的样品界限。我们得出了高斯矢量条目之间部分相关性的类似结果。 \ end {摘要}
We provide finite sample bounds on the Normal approximation to the law of the least squares estimator of the projection parameters normalized by the sandwich-based standard errors. Our results hold in the increasing dimension setting and under minimal assumptions on the data generating distribution. In particular, we do not assume a linear regression function and only require the existence of finitely many moments for the response and the covariates. Furthermore, we construct confidence sets for the projection parameters in the form of hyper-rectangles and establish finite sample bounds on their coverage and accuracy. We derive analogous results for partial correlations among the entries of sub-Gaussian vectors. \end{abstract}
