It is clear that conventional statistical inference protocols need to be revised to deal correctly with the high-dimensional data that are now common. Most recent studies aimed at achieving this revision rely on powerful approximation techniques, that call for rigorous results against which they can be tested. In this context, the simplest case of high-dimensional linear regression has acquired significant new relevance and attention. In this paper we use the statistical physics perspective on inference to derive a number of new exact results for linear regression in the high-dimensional regime.
翻译:显然,常规的统计推理规程需要修订,以便正确处理目前常见的高维数据,最近旨在实现这一修订的研究大多依靠强大的近似技术,这些技术需要严格的近似技术来测试这些数据。在这方面,最简单的高维线性回归案例已获得新的重大相关性和关注。在本文件中,我们从统计物理学的角度推断高维体系线性回归的一些新的精确结果。