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09/06/2023
Denoising and Multilinear Dimension-Reduction of High-Dimensional Matrix-Variate Time Series via a Factor Model
This paper proposes a new multilinear projection method for dimension-re...
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07/15/2023
Supervised Dynamic PCA: Linear Dynamic Forecasting with Many Predictors
This paper proposes a novel dynamic forecasting method using a new super...
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07/07/2023
Scalable High-Dimensional Multivariate Linear Regression for Feature-Distributed Data
Feature-distributed data, referred to data partitioned by features and s...
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04/24/2023
Determination of the effective cointegration rank in high-dimensional time-series predictive regressions
This paper proposes a new approach to identifying the effective cointegr...
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07/23/2021
Robust Estimation of High-Dimensional Vector Autoregressive Models
High-dimensional time series data appear in many scientific areas in the...
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03/26/2021
Divide-and-Conquer: A Distributed Hierarchical Factor Approach to Modeling Large-Scale Time Series Data
This paper proposes a hierarchical approximate-factor approach to analyz...
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11/18/2020
A Two-Way Transformed Factor Model for Matrix-Variate Time Series
We propose a new framework for modeling high-dimensional matrix-variate ...
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05/05/2020
Modeling High-Dimensional Unit-Root Time Series
In this paper, we propose a new procedure to build a structural-factor m...
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06/12/2019
Tensor Canonical Correlation Analysis
In many applications, such as classification of images or videos, it is ...
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08/23/2018
Structural-Factor Modeling of High-Dimensional Time Series: Another Look at Approximate Factor Models with Diverging Eigenvalues
This article proposes a new approach to modeling high-dimensional time s...
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08/20/2018
A Structural-Factor Approach to Modeling High-Dimensional Time Series
This paper considers a structural-factor approach to modeling high-dimen...
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12/31/2017