1.5k citations · 7.9k across the 139 of their papers we have counts for
6 papers · 2 filters
Partial Consistency with Sparse Incidental Parameters
Jianqing Fan, Runlong Tang, Xiaofeng Shi
Penalized estimation principle is fundamental to high-dimensional problems. In the literature, it has been extensively and successfully applied to various models with only structur…
Strong oracle optimality of folded concave penalized estimation
Jianqing Fan, Lingzhou Xue, Hui Zou
Folded concave penalization methods have been shown to enjoy the strong oracle property for high-dimensional sparse estimation. However, a folded concave penalization problem usual…
Conditional Sure Independence Screening
Emre Barut, Jianqing Fan, Anneleen Verhasselt
Independence screening is a powerful method for variable selection for `Big Data' when the number of variables is massive. Commonly used independence screening methods are based on…
Adaptive robust variable selection
Jianqing Fan, Yingying Fan, Emre Barut
Heavy-tailed high-dimensional data are commonly encountered in various scientific fields and pose great challenges to modern statistical analysis. A natural procedure to address th…
Endogeneity in high dimensions
Jianqing Fan, Yuan Liao
Most papers on high-dimensional statistics are based on the assumption that none of the regressors are correlated with the regression error, namely, they are exogenous. Yet, endoge…
Large Covariance Estimation by Thresholding Principal Orthogonal Complements
Jianqing Fan, Yuan Liao, Martina Mincheva
This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matr…