15 citations · 47 across the 30 of their papers we have counts for
13 papers · 1 filter
Nonparametric Quantile Regression for Homogeneity Pursuit in Panel Data Models
Xiaoyu Zhang, Di Wang, Heng Lian +1
Many panel data have the latent subgroup effect on individuals, and it is important to correctly identify these groups since the efficiency of resulting estimators can be improved…
High-dimensional vector autoregressive time series modeling via tensor decomposition
Di Wang, Yao Zheng, Heng Lian +1
The classical vector autoregressive model is a fundamental tool for multivariate time series analysis. However, it involves too many parameters when the number of time series and l…
Variable Selection and Estimation for Partially Linear Single-index Models with Longitudinal Data
Gaorong Li, Peng Lai, Heng Lian
In this paper, we consider the partially linear single-index models with longitudinal data. To deal with the variable selection problem in this context, we propose a penalized proc…
Minimax Prediction for Functional Linear Regression with Functional Responses in Reproducing Kernel Hilbert Spaces
Heng Lian
In this article, we consider convergence rates in functional linear regression with functional responses, where the linear coefficient lies in a reproducing kernel Hilbert space (R…
Shrinkage Estimation and Selection for Multiple Functional Regression
Heng Lian
Functional linear regression is a useful extension of simple linear regression and has been investigated by many researchers. However, functional variable selection problems when m…
Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data
Peng Lai, Qihua Wang, Heng Lian
In this paper, we present a generalized estimating equations based estimation approach and a variable selection procedure for single-index models when the observed data are cluster…
Semiparametric Bayesian Information Criterion for Model Selection in Ultra-high Dimensional Additive Models
Heng Lian
For linear models with a diverging number of parameters, it has recently been shown that modified versions of Bayesian information criterion (BIC) can identify the true model consi…
Gaussian process single-index models as emulators for computer experiments
Robert B. Gramacy, Heng Lian
A single-index model (SIM) provides for parsimonious multi-dimensional nonlinear regression by combining parametric (linear) projection with univariate nonparametric (non-linear) r…
Flexible Shrinkage Estimation in High-Dimensional Varying Coefficient Models
Heng Lian
We consider the problem of simultaneous variable selection and constant coefficient identification in high-dimensional varying coefficient models based on B-spline basis expansion.…
Sparse Bayesian Hierarchical Modeling of High-dimensional Clustering Problems
Heng Lian
Clustering is one of the most widely used procedures in the analysis of microarray data, for example with the goal of discovering cancer subtypes based on observed heterogeneity of…
Empirical Likelihood Confidence Intervals for Nonparametric Functional Data Analysis
Heng Lian
We consider the problem of constructing confidence intervals for nonparametric functional data analysis using empirical likelihood. In this doubly infinite-dimensional context, we…
Nonparametric Estimation of Variance Function for Functional Data
Heng Lian
This article investigates nonparametric estimation of variance functions for functional data when the mean function is unknown. We obtain asymptotic results for the kernel estimato…
A note on conditional Akaike information for Poisson regression with random effects
Heng Lian
A popular model selection approach for generalized linear mixed-effects models is the Akaike information criterion, or AIC. Among others, \cite{vaida05} pointed out the distinction…