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20182020
most citedNetwork-Assisted Estimation for Large-dimensional Factor Model with Guaranteed Convergence Rate Improvement

1 citations · 1 across the 2 of their papers we have counts for

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stat.ME2020

Simultaneous Differential Network Analysis and Classification for High-dimensional Matrix-variate Data, with application to Brain Connectivity Alteration Detection and fMRI-guided Medical Diagnoses of Alzheimer's Disease

Chen Hao, Guo Ying, He Yong +6

Alzheimer's disease (AD) is the most common form of dementia, which causes problems with memory, thinking and behavior. Growing evidence has shown that the brain connectivity netwo…

stat.ME2020

Projected Estimation for Large-dimensional Matrix Factor Models

Long Yu, Yong He, Xin-bing Kong +1

In this study, we propose a projection estimation method for large-dimensional matrix factor models with cross-sectionally spiked eigenvalues. By projecting the observation matrix…

stat.ME20201 cited

Network-Assisted Estimation for Large-dimensional Factor Model with Guaranteed Convergence Rate Improvement

Long Yu, Yong He, Xinsheng Zhang +1

Network structure is growing popular for capturing the intrinsic relationship between large-scale variables. In the paper we propose to improve the estimation accuracy for large-di…

stat.ME2019

Large-dimensional Factor Analysis without Moment Constraints

Yong He, Xinbing Kong, Long Yu +1

Large-dimensional factor model has drawn much attention in the big-data era, in order to reduce the dimensionality and extract underlying features using a few latent common factors…

stat.ME2018

Robust Factor Number Specification for Large-dimensional Elliptical Factor Model

Long Yu, Yong He, Xinsheng Zhang

The accurate specification of the number of factors is critical to the validity of factor models and the topic almost occupies the central position in factor analysis. Plenty of es…