Linear Regression Beyond Covariance: Latent Slope Spectra from Higher-Order Cumulants
超越协方差的线性回归:高阶累积量中的潜在斜率谱
Least squares summarizes the joint distribution of a response and regressor through second-order information. When an observed regressor is composed of latent components carrying different relationships with the response, this summary can average over distinct linear effects. We study the additional linear information contained in higher-order mixed cumulants and formalize it through the latent slope spectrum. Ordinary least squares is a variance-weighted barycenter of this…