activity
20182023
most citedMatrix Factor Analysis: From Least Squares to Iterative Projection

5 citations · 27 across the 18 of their papers we have counts for

collaborators
Showing 2023 · stat.MEShow all

5 papers · 2 filters

stat.ME2023★ 1 cited

Robust Statistical Inference for Large-dimensional Matrix-valued Time Series via Iterative Huber Regression

Yong He, Xin-Bing Kong, Dong Liu +1

Matrix factor model is drawing growing attention for simultaneous two-way dimension reduction of well-structured matrix-valued observations. This paper focuses on robust statistica…

stat.ME2023★ 1 cited

Simultaneous Estimation and Dataset Selection for Transfer Learning in High Dimensions by a Non-convex Penalty

Zeyu Li, Dong Liu, Yong He +1

In this paper, we propose to estimate model parameters and identify informative source datasets simultaneously for high-dimensional transfer learning problems with the aid of a non…

stat.ME2023★ 4 cited

Huber Principal Component Analysis for Large-dimensional Factor Models

Yong He, Lingxiao Li, Dong Liu +1

Factor models have been widely used in economics and finance. However, the heavy-tailed nature of macroeconomic and financial data is often neglected in the existing literature. To…

stat.ME2023★ 1 cited

Robust Tensor Factor Analysis

Matteo Barigozzi, Yong He, Lingxiao Li +1

We consider (robust) inference in the context of a factor model for tensor-valued sequences. We study the consistency of the estimated common factors and loadings space when using…

stat.ME2023

An Efficient Iterative Least Squares Algorithm for Large-dimensional Matrix Factor Model via Random Projection

Yong He, Ran Zhao, Wen-Xin Zhou

The matrix factor model has drawn growing attention for its advantage in achieving two-directional dimension reduction simultaneously for matrix-structured observations. In this pa…