-Penalized Pairwise Difference Estimation for a High-Dimensional Censored Regression Model
高维删失回归模型的 ℓ1 惩罚成对差分估计
High-dimensional data are nowadays readily available and increasingly common in various fields of empirical economics. This article considers estimation and model selection for a high-dimensional censored linear regression model. We combine l1-penalization method with the ideas of pairwise difference and propose an l1-penalized pairwise difference least absolute deviations (LAD) estimator. Estimation consistency and model selection consistency of the estimator are…