Published November 2, 2023 | Version v1
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Matrix-Variate Time Series Analysis: A Brief Review and Some New Developments

  • 1. University of Chicago

Description

This paper briefly reviews the recent research in matrix-variate time series analysis, discusses some new developments, especially for seasonal time series, and demonstrates some applications. A general matrix autoregressive moving-average model is introduced. The paper narrates a simple approach for understanding the model, identifiability issues, and estimation. Real examples are used to illustrate the theory.

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Matrix‐Variate-Time-Series-Analysis.pdf

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Additional details

Identifiers

DOI
10.1111/insr.12558
Other
oai:uchicago.tind.io:9552

UChicago Information

Division(s)
Booth School of Business
Department(s)
Econometrics and Statistics