In observational studies, regression coefficients for categorical regressors are overwhelmingly presented in terms of contrasts with a reference category. For unordered regressors with many categories
We propose an algorithm, semismooth Newton coordinate descent (SNCD), for the elastic-net penalized Huber loss regression and quantile regression in high dimensional settings. Unlike existing coordina
