activity
20072018
most citedReduced-rank Regression in Sparse Multivariate Varying-Coefficient Models with High-dimensional Covariates

8 citations · 12 across the 11 of their papers we have counts for

collaborators

11 papers

stat.ME2018★ 1 cited

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…

stat.ME2017★ 1 cited

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…

stat.ME2015★ 1 cited

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…

stat.AP2013

Letter to the Editor

Yuao Hu, Ye Tian, Heng Lian

The paper by Alfons, Croux and Gelper (2013), Sparse least trimmed squares regression for analyzing high-dimensional large data sets, considered a combination of least trimmed squa…

stat.ME2013★ 8 cited

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…

stat.ME2010

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…