论文标题
葡萄藤基于高维控制的仿制生成
Vine copula based knockoff generation for high-dimensional controlled variable selection
论文作者
论文摘要
葡萄藤是用于高维依赖建模的灵活工具。在本文中，我们讨论了用葡萄藤的生成近似模型ockoffs。它显示了如何将高斯仿冒品推广到高斯copula仿冒品。参数化高斯copulas的一种方便方法是部分相关藤蔓。我们讨论了部分相关葡萄藤的完成问题与高斯仿冒品是如何相关的。部分相关葡萄藤的自然概括是藤蔓小孢子，非常适合生成近似模型X仿型。我们讨论了特定的D-vine结构，该结构是获得藤蔓coplakoff模型的优势。在一项仿真研究中，我们证明了藤蔓型仿制模型对于高维控制变量选择有效且有效。
Vine copulas are a flexible tool for high-dimensional dependence modeling. In this article, we discuss the generation of approximate model-X knockoffs with vine copulas. It is shown how Gaussian knockoffs can be generalized to Gaussian copula knockoffs. A convenient way to parametrize Gaussian copulas are partial correlation vines. We discuss how completion problems for partial correlation vines are related to Gaussian knockoffs. A natural generalization of partial correlation vines are vine copulas which are well suited for the generation of approximate model-X knockoffs. We discuss a specific D-vine structure which is advantageous to obtain vine copula knockoff models. In a simulation study, we demonstrate that vine copula knockoff models are effective and powerful for high-dimensional controlled variable selection.
