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20172026
most citedRank Determination in Tensor Factor Model

33 citations · 65 across the 8 of their papers we have counts for

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7 papers · 1 filter

stat.ME2026

Reduced-Rank Autoregressive Models for Matrix Time Series

Han Xiao, Yuefeng Han, Rong Chen +1

Matrix time series is a series of matrix data observed over time. Analytical tools for such time series is needed in many applications in finance, economics, engineering and many o…

stat.ME2025

Threshold Tensor Factor Model in CP Form

Stevenson Bolivar, Rong Chen, Yuefeng Han

This paper proposes a new Threshold Tensor Factor Model in Canonical Polyadic (CP) form for tensor time series. By integrating a thresholding autoregressive structure for the laten…

stat.ME2024★ 2 cited

Dynamic Matrix Factor Models for High Dimensional Time Series

Ruofan Yu, Rong Chen, Han Xiao +1

Matrix time series, which consist of matrix-valued data observed over time, are prevalent in various fields such as economics, finance, and engineering. Such matrix time series dat…

stat.ME2021

CP Factor Model for Dynamic Tensors

Yuefeng Han, Dan Yang, Cun-Hui Zhang +1

Observations in various applications are frequently represented as a time series of multidimensional arrays, called tensor time series, preserving the inherent multidimensional str…

stat.ME2021

Simultaneous Decorrelation of Matrix Time Series

Yuefeng Han, Rong Chen, Cun-Hui Zhang +1

We propose a contemporaneous bilinear transformation for a matrix time series to alleviate the difficulties in modeling and forecasting matrix time series when and/…

stat.ME2020★ 33 cited

Rank Determination in Tensor Factor Model

Yuefeng Han, Rong Chen, Cun-Hui Zhang

Factor model is an appealing and effective analytic tool for high-dimensional time series, with a wide range of applications in economics, finance and statistics. This paper develo…

stat.ME2020★ 14 cited

Tensor Factor Model Estimation by Iterative Projection

Yuefeng Han, Rong Chen, Dan Yang +1

Tensor time series, which is a time series consisting of tensorial observations, has become ubiquitous. It typically exhibits high dimensionality. One approach for dimension reduct…