10 citations · 26 across the 6 of their papers we have counts for
6 papers
High-Dimensional Vector Autoregression with Common Response and Predictor Factors
Di Wang, Xiaoyu Zhang, Guodong Li +1
The reduced-rank vector autoregressive (VAR) model can be interpreted as a supervised factor model, where two factor modelings are simultaneously applied to response and predictor…
Rate-Optimal Robust Estimation of High-Dimensional Vector Autoregressive Models
Di Wang, Ruey S. Tsay
High-dimensional time series data appear in many scientific areas in the current data-rich environment. Analysis of such data poses new challenges to data analysts because of not o…
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 Low-Rank Tensor Autoregressive Time Series Modeling
Di Wang, Yao Zheng, Guodong Li
Modern technological advances have enabled an unprecedented amount of structured data with complex temporal dependence, urging the need for new methods to efficiently model and for…
Compact Autoregressive Network
Di Wang, Feiqing Huang, Jingyu Zhao +2
Autoregressive networks can achieve promising performance in many sequence modeling tasks with short-range dependence. However, when handling high-dimensional inputs and outputs, t…
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…