Probabilistic Reduced-Dimensional Vector Autoregressive Modeling for Dynamics Prediction and Reconstruction with Oblique Projections-Reference-Cited by-同舟云学术

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Probabilistic Reduced-Dimensional Vector Autoregressive Modeling for Dynamics Prediction and Reconstruction with Oblique Projections

Published:2023-12-13 Issue: Volume: Page:7623-7628
ISSN:
Container-title:2023 62nd IEEE Conference on Decision and Control (CDC)
language:
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Author:

Mo Yanfang¹,Yu Jiaxin²,Qin S. Joe³

Affiliation:

1. Hong Kong Institute for Data Science, City University of Hong Kong,Hong Kong

2. School of Data Science and Hong Kong Institute for Data Science, City University of Hong Kong,Hong Kong

3. Institute of Data Science, Lingnan University,Department of Computing and Decision Science,Hong Kong

Funder

Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10383192/10383193/10384177.pdf?arnumber=10384177

Reference25 articles.

1. Control Oriented Learning in the Era of Big Data

2. Identifying a Simplifying Structure in Time Series

3. Bridging systems theory and data science: A unifying review of dynamic latent variable analytics and process monitoring

4. Modeling High-Dimensional Time Series: A Factor Model With Dynamically Dependent Factors and Diverging Eigenvalues

5. Multivariate Reduced-Rank Regression

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