We propose a penalized quantile regression and an independence screening procedure to identify important covariates and to exclude unimportant ones for a general class of ultrahigh dimensional single ...

Analysis of high-dimensional data often seeks to identify a subset of important features and to assess the effects of these features on outcomes. Traditional statistical inference procedures based on ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single ...