The least angle regression (LAR) was proposed by Efron, Hastie, Johnstone and Tibshirani in the year 2004 for continuous model selection in linear regression. It is motivated by a geometric argument a
Results of the medium-dimensional setting with independet correlation structure of the simulation study in "Variable selection in linear regression models: choosing the best subset is not always t
Modern high-dimensional statistical inference often faces the problem of missing data. In recent decades, many studies have focused on this topic and provided strategies including complete-sample anal
