Drawing Inferences for High-Dimensional Linear Models: A Selection-Assisted Partial Regression and Smoothing Approach
Drawing Inferences for High-Dimensional Linear Models: A Selection-Assisted Partial Regression and Smoothing Approach
Drawing inferences for high-dimensional models is challenging as regular asymptotic theories are not applicable. This article proposes a new framework of simultaneous estimation and inferences for high-dimensional linear models. By smoothing over partial regression estimates based on a given variable selection scheme, we reduce the problem to low-dimensional least squares …