2016
Maximum Likelihood for Variance Estimation in High-Dimensional Linear Models
AISTATS 2016poster
We study maximum likelihood estimators (MLEs) for the residual variance, the signal-to-noise ratio, and other variance parameters in high-dimensional linear models. These parameters are essential in many statistical applications involving regression diagnostics, inference, tuning parameter select…