185 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of Electronic Science and Technology of ChinaCN23 papers
- Sichuan UniversityCN18 papers
- University of Hong KongHK11 papers
- London School of Economics and Political ScienceGB9 papers
- Southwest Jiaotong UniversityCN9 papers
- University of GroningenNL8 papers
- Hong Kong Polytechnic UniversityHK6 papers
- The University of MelbourneAU6 papers
- University of PittsburghUS6 papers
- Chengdu UniversityCN5 papers
- Chinese Academy of SciencesCN5 papers
- Hong Kong University of Science and TechnologyHK5 papers
15 papers · 1 filter
Edge differentially private estimation in the -model via jittering and method of moments
Jinyuan Chang, Qiao Hu, Eric D. Kolaczyk +2
A standing challenge in data privacy is the trade-off between the level of privacy and the efficiency of statistical inference. Here we conduct an in-depth study of this trade-off…
Central limit theorems for high dimensional dependent data
Jinyuan Chang, Xiaohui Chen, Mingcong Wu
Motivated by statistical inference problems in high-dimensional time series data analysis, we first derive non-asymptotic error bounds for Gaussian approximations of sums of high-d…
An autocovariance-based learning framework for high-dimensional functional time series
Jinyuan Chang, Cheng Chen, Xinghao Qiao +1
Many scientific and economic applications involve the statistical learning of high-dimensional functional time series, where the number of functional variables is comparable to, or…
Learning rates for partially linear support vector machine in high dimensions
Yifan Xia, Yongchao Hou, Shaogao Lv
This paper analyzes a new regularized learning scheme for high dimensional partially linear support vector machine. The proposed approach consists of an empirical risk and the Lass…
Optimal covariance matrix estimation for high-dimensional noise in high-frequency data
Jinyuan Chang, Qiao Hu, Cheng Liu +1
We consider high-dimensional measurement errors with high-frequency data. Our objective is on recovering the high-dimensional cross-sectional covariance matrix of the random errors…
A frequency domain analysis of the error distribution from noisy high-frequency data
Jinyuan Chang, Aurore Delaigle, Peter Hall +1
Data observed at high sampling frequency are typically assumed to be an additive composite of a relatively slow-varying continuous-time component, a latent stochastic process or a…
A new scope of penalized empirical likelihood with high-dimensional estimating equations
Jinyuan Chang, Cheng Yong Tang, Tong Tong Wu
Statistical methods with empirical likelihood (EL) are appealing and effective especially in conjunction with estimating equations through which useful data information can be adap…
Estimation for single-index and partially linear single-index integrated models
Chaohua Dong, Jiti Gao, Dag Tjøstheim
Estimation mainly for two classes of popular models, single-index and partially linear single-index models, is studied in this paper. Such models feature nonstationarity. Orthogona…
Bayesian Multiple Testing Under Sparsity for Polynomial-Tailed Distributions
Xueying Tang, Ke Li, Malay Ghosh
This paper considers Bayesian multiple testing under sparsity for polynomial-tailed distributions satisfying a monotone likelihood ratio property. Included in this class of distrib…
Double-bootstrap methods that use a single double-bootstrap simulation
Jinyuan Chang, Peter Hall
We show that, when the double bootstrap is used to improve performance of bootstrap methods for bias correction, techniques based on using a single double-bootstrap sample for each…
Cramér-type moderate deviations for Studentized two-sample -statistics with applications
Jinyuan Chang, Qi-Man Shao, Wen-Xin Zhou
Two-sample -statistics are widely used in a broad range of applications, including those in the fields of biostatistics and econometrics. In this paper, we establish sharp Cramé…
Simulation-Based Hypothesis Testing of High Dimensional Means Under Covariance Heterogeneity
Jinyuan Chang, Chao Zheng, Wen-Xin Zhou +1
In this paper, we study the problem of testing the mean vectors of high dimensional data in both one-sample and two-sample cases. The proposed testing procedures employ maximum-typ…
High dimensional generalized empirical likelihood for moment restrictions with dependent data
Jinyuan Chang, Song Xi Chen, Xiaohong Chen
This paper considers the maximum generalized empirical likelihood (GEL) estimation and inference on parameters identified by high dimensional moment restrictions with weakly depend…
Nonparametric Independence Screening in Sparse Ultra-High Dimensional Varying Coefficient Models
Jianqing Fan, Yunbei Ma, Wei Dai
The varying-coefficient model is an important nonparametric statistical model that allows us to examine how the effects of covariates vary with exposure variables. When the number…
Contour projected dimension reduction
Ronghua Luo, Hansheng Wang, Chih-Ling Tsai
In regression analysis, we employ contour projection (CP) to develop a new dimension reduction theory. Accordingly, we introduce the notions of the central contour subspace and gen…