周岭｜西南财经大学｜学者主页

期刊论文

2026

Supervised Random Feature Regression via Projection Pursuit

Jingran Zhou, Ling Zhou, Shaogao Lv

The American Statistician

DOI

2025

Spatial effect detection regression for large-scale spatio-temporal covariates

Chenlin Zhang, Ling Zhou, Bin Guo, Huazhen Lin

Journal of the Royal Statistical Society Series B (Statistical Methodology)

DOI

2025

High-dimensional large-scale mixed-type data imputation under missing at random

Wei Liu, LI Gui-zhen, Ling Zhou, Lan Luo

Science China Mathematics

DOI

2025

Identification of Latent Subgroups for Time-Varying Panel Data Models

Ye He, Qing Luo, Liu Liu, Shengzhi Mao, Ling Zhou

Journal of Business and Economic Statistics

DOI

2025

Inference for High-Dimensional Streamed Longitudinal Data

Senyuan Zheng, Ling Zhou

Acta Mathematica Sinica English Series

DOI

2024

Deep Regression Learning with Optimal Loss Function

Xuancheng Wang, Ling Zhou, Huazhen Lin

Journal of the American Statistical Association

DOI

2024

Comments on: Data integration via analysis of subspaces (DIVAS)

Ling Zhou, Peter X.‐K. Song

Test

DOI

2024

Supervised homogeneity fusion: A combinatorial approach

Wen Wang, Shihao Wu, Ziwei Zhu, Ling Zhou, Peter X.‐K. Song

The Annals of Statistics

DOI

2024

Subgroup learning for multiple mixed-type outcomes with block-structured covariates

Xun Zhao, Lu Tang, Weijia Zhang, Ling Zhou

Computational Statistics & Data Analysis

DOI

2024

Tensor Decomposition-assisted Multiview Subgroup Analysis

Xun Zhao, Ling Zhou, Wei Zhang, Hua Zhen Lin

Acta Mathematica Sinica English Series

DOI

2024

Transfer learning via random forests: A one-shot federated approach

Pengcheng Xiang, Ling Zhou, Lu Tang

Computational Statistics & Data Analysis

DOI

2023

Discussion of ‘Statistical inference for streamed longitudinal data’

Peter X.‐K. Song, Ling Zhou

Biometrika

DOI

2023

Online missing value imputation for high-dimensional mixed-type data via generalized factor models

Wei Liu, Lan Luo, Ling Zhou

Computational Statistics & Data Analysis

DOI

2023

Distributed Computing and Inference for Big Data

Ling Zhou, Ziyang Gong, Pengcheng Xiang

Annual Review of Statistics and Its Application

DOI

2022

Real-Time Regression Analysis of Streaming Clustered Data With Possible Abnormal Data Batches

Lan Luo, Ling Zhou, Peter X.‐K. Song

Journal of the American Statistical Association

DOI

2022

Center-Augmented ℓ2-Type Regularization for Subgroup Learning

Ye He, Ling Zhou, Yingcun Xia, Huazhen Lin

Biometrics

DOI

2022

A discussion on “A selective review of statistical methods using calibration information from similar studies”

Ling Zhou, Peter X.‐K. Song

Statistical Theory and Related Fields

DOI

2022

Subgroup-effects models for the analysis of personal treatment effects

Ling Zhou, Shiquan Sun, Haoda Fu, Peter X.‐K. Song

The Annals of Applied Statistics

DOI

2019

Efficient estimation and computation of parameters and nonparametric functions in generalized semi/non-parametric regression models

Ling Zhou, Huazhen Lin, Kani Chen, Hua Liang

Journal Of Econometrics，Vol. 2130, No. 2

DOI

2019

Distributed simultaneous inference in generalized linear models via confidence distribution

Lu Tang, Ling Zhou, Peter X.‐K. Song

Journal of Multivariate Analysis

DOI

2019

Global kernel estimator and test of varying‐coefficient autoregressive model

Huazhen Lin, Baoying Yang, Ling Zhou, PAUL S. F. YIP, Ying‐Yeh Chen, Hua Liang

Canadian Journal of Statistics

DOI

2019

Evaluating functional covariate‐environment interactions in the Cox regression model

Ling Zhou, Haoqi Li, Huazhen Lin, Peter X.‐K. Song

Canadian Journal of Statistics

DOI

2017

Efficient Estimation of the Nonparametric Mean and Covariance Functions for Longitudinal and Sparse Functional Data

Ling Zhou, Huazhen Lin, Hua Liang

Journal of the American Statistical Association

DOI

2016

Education, Intelligence, and Well-Being: Evidence from a Semiparametric Latent Variable Transformation Model for Multiple Outcomes of Mixed Types

Ling Zhou, Huazhen Lin, Yi-Chen Lin

Social Indicators Research，Vol. 125, No. 3

DOI

2014

Semiparametric transformation models for semicompeting survival data

Huazhen Lin, Ling Zhou, Chunhong Li, Yi Li

Biometrics

DOI

2014

Semiparametric Regression Analysis of Longitudinal Skewed Data

Huazhen Lin, Ling Zhou, Xiao‐Hua Zhou

Scandinavian Journal of Statistics

DOI

2014

Selection of Latent Variables for Multiple Mixed‐outcome Models

Ling Zhou, Huazhen Lin, Xinyuan Song, Yi Li

Scandinavian Journal of Statistics

DOI

2013

Semiparametric latent variable transformation models for multiple mixed outcomes

Huazhen Lin, Ling Zhou, Yi Li, Robert M. Elashoff

Statistica Sinica

DOI

预印本

2026

Synergistic Learning in Domain Adaptation with a Known Link: A Minimax Understanding

Pengcheng Xiang, Ling Zhou, Yuhong Yang

arXiv preprint

2026

Neural Network Machine Regression (NNMR): A Deep Learning Framework for Uncovering High-order Synergistic Effects

Jiuchen Zhang, Ling Zhou, Peter Song

arXiv preprint

2026

Model-Assisted Causal Inference for the Treatment Effect on Recurrent Events in the Presence of Terminal Events

Yiyuan Huang, Ling Zhou, Min Zhang, Peter X. K. Song

arXiv preprint

2025

On a synergistic learning phenomenon in nonparametric domain adaptation

Ling Zhou, Yuhong Yang

arXiv preprint

2021

A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources

Xiaoqing Tan, Chung-Chou H. Chang, Ling Zhou, Lu Tang

arXiv preprint

2019

Method of Contraction-Expansion (MOCE) for Simultaneous Inference in Linear Models

Fei Wang, Ling Zhou, Lu Tang, Peter X. -K. Song

arXiv preprint

2017

Scalable and Efficient Statistical Inference with Estimating Functions in the MapReduce Paradigm for Big Data

Ling Zhou, Peter X. -K. Song

arXiv preprint

2012

Multi-dimensional central limit theorems and laws of large numbers under sublinear expectations

Ze-Chun Hu, Ling Zhou

arXiv preprint

2011

Chebyshev's inequality for Banach-space-valued random elements

Ling Zhou, Ze-Chun Hu

arXiv preprint

精选作品

期刊论文

Supervised Random Feature Regression via Projection Pursuit

Spatial effect detection regression for large-scale spatio-temporal covariates

High-dimensional large-scale mixed-type data imputation under missing at random

Identification of Latent Subgroups for Time-Varying Panel Data Models

Inference for High-Dimensional Streamed Longitudinal Data

Deep Regression Learning with Optimal Loss Function

Comments on: Data integration via analysis of subspaces (DIVAS)

Supervised homogeneity fusion: A combinatorial approach

Subgroup learning for multiple mixed-type outcomes with block-structured covariates

Tensor Decomposition-assisted Multiview Subgroup Analysis

Transfer learning via random forests: A one-shot federated approach

Discussion of ‘Statistical inference for streamed longitudinal data’

Online missing value imputation for high-dimensional mixed-type data via generalized factor models

Distributed Computing and Inference for Big Data

Real-Time Regression Analysis of Streaming Clustered Data With Possible Abnormal Data Batches

Center-Augmented ℓ2-Type Regularization for Subgroup Learning

A discussion on “A selective review of statistical methods using calibration information from similar studies”

Subgroup-effects models for the analysis of personal treatment effects

Efficient estimation and computation of parameters and nonparametric functions in generalized semi/non-parametric regression models

Distributed simultaneous inference in generalized linear models via confidence distribution

Global kernel estimator and test of varying‐coefficient autoregressive model

Evaluating functional covariate‐environment interactions in the Cox regression model

Efficient Estimation of the Nonparametric Mean and Covariance Functions for Longitudinal and Sparse Functional Data

Education, Intelligence, and Well-Being: Evidence from a Semiparametric Latent Variable Transformation Model for Multiple Outcomes of Mixed Types

Semiparametric transformation models for semicompeting survival data

Semiparametric Regression Analysis of Longitudinal Skewed Data

Selection of Latent Variables for Multiple Mixed‐outcome Models

Semiparametric latent variable transformation models for multiple mixed outcomes

预印本

Synergistic Learning in Domain Adaptation with a Known Link: A Minimax Understanding

Neural Network Machine Regression (NNMR): A Deep Learning Framework for Uncovering High-order Synergistic Effects

Model-Assisted Causal Inference for the Treatment Effect on Recurrent Events in the Presence of Terminal Events

On a synergistic learning phenomenon in nonparametric domain adaptation

A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources

Method of Contraction-Expansion (MOCE) for Simultaneous Inference in Linear Models

Scalable and Efficient Statistical Inference with Estimating Functions in the MapReduce Paradigm for Big Data

Multi-dimensional central limit theorems and laws of large numbers under sublinear expectations

Chebyshev's inequality for Banach-space-valued random elements

研究方向