Many exciting results have been obtained on model selection for high-dimensional data in both efficient algorithms and theoretical developments. The powerful penalized regression methods can give spar
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
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