5 papers
Penalized Principal Component Analysis for Large-dimension Factor Model with Group Pursuit
Yong He, Dong Liu, Guangming Pan +1
This paper investigates the intrinsic group structures within the framework of large-dimensional approximate factor models, which portrays homogeneous effects of the common factors…
TransPCA for Large-dimensional Factor Analysis with Weak Factors: Power Enhancement via Knowledge Transfer
Yong He, Dong Liu, Yunjing Sun +1
Early work established convergence of the principal component estimators of the factors and loadings up to a rotation for large dimensional approximate factor models with weak fact…
Factor Modelling for Biclustering Large-dimensional Matrix-valued Time Series
Yong He, Xiaoyang Ma, Xingheng Wang +1
A novel unsupervised learning method is proposed in this paper for biclustering large-dimensional matrix-valued time series based on an entirely new latent two-way factor structure…
Generalized Principal Component Analysis for Large-dimensional Matrix Factor Model
Yong He, Yujie Hou, Haixia Liu +1
Matrix factor models have been growing popular dimension reduction tools for large-dimensional matrix time series. However, the heteroscedasticity of the idiosyncratic components h…
Large-dimensional Robust Factor Analysis with Group Structure
Yong He, Xiaoyang Ma, Xingheng Wang +1
In this paper, we focus on exploiting the group structure for large-dimensional factor models, which captures the homogeneous effects of common factors on individuals within the sa…