8 citations · 12 across the 11 of their papers we have counts for
7 papers · 1 filter
A General Framework For Frequentist Model Averaging
Priyam Mitra, Heng Lian, Ritwik Mitra +2
Model selection strategies have been routinely employed to determine a model for data analysis in statistics, and further study and inference then often proceed as though the selec…
Additive Partially Linear Models for Massive Heterogeneous Data
Binhuan Wang, Yixin Fang, Heng Lian +1
We consider an additive partially linear framework for modelling massive heterogeneous data. The major goal is to extract multiple common features simultaneously across all sub-pop…
Greedy Forward Regression for Variable Screening
Ming-Yen Cheng, Sanying Feng, Gaorong Li +1
Two popular variable screening methods under the ultra-high dimensional setting with the desirable sure screening property are the sure independence screening (SIS) and the forward…
Reduced-rank Regression in Sparse Multivariate Varying-Coefficient Models with High-dimensional Covariates
Heng Lian, Shujie Ma
In genetic studies, not only can the number of predictors obtained from microarray measurements be extremely large, there can also be multiple response variables. Motivated by such…
Gaussian Process Models for Nonparametric Functional Regression with Functional Responses
Heng Lian
Recently nonparametric functional model with functional responses has been proposed within the functional reproducing kernel Hilbert spaces (fRKHS) framework. Motivated by its supe…
Shrinkage Tuning Parameter Selection in Precision Matrices Estimation
Heng Lian
Recent literature provides many computational and modeling approaches for covariance matrices estimation in a penalized Gaussian graphical models but relatively little study has be…