Multiple Change Points Detection in Low Rank and Sparse High Dimensional Vector Autoregressive Models

Author:

Bai PeiliangORCID,Safikhani AbolfazlORCID,Michailidis GeorgeORCID

Funder

NSF

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Signal Processing

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. High-Dimensional Time Series Segmentation via Factor-Adjusted Vector Autoregressive Modeling;Journal of the American Statistical Association;2023-07-26

2. Synchronous Development Strategy of China’s New Four Modernizations: An Analysis Based on Interactive Mode;IEEE Access;2023

3. Spectral Dependence;Econometrics and Statistics;2022-11

4. Multiple Change Point Detection in Reduced Rank High Dimensional Vector Autoregressive Models;Journal of the American Statistical Association;2022-06-06

5. Granger Causality: A Review and Recent Advances;Annual Review of Statistics and Its Application;2021-11-17

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