# Forecasting Multilinear Data via Transform-Based Tensor Autoregression

@article{Cates2022ForecastingMD,
title={Forecasting Multilinear Data via Transform-Based Tensor Autoregression},
author={Jackson Cates and Randy C. Hoover and Kyle A. Caudle and Cagri Ozdemir and Karen S. Braman and David Machette},
journal={ArXiv},
year={2022},
volume={abs/2205.12201}
}
• Published 24 May 2022
• Computer Science
• ArXiv
In the era of big data, there is an increasing demand for new methods for analyzing and forecasting 2-dimensional data. The current research aims to accomplish these goals through the combination of time-series modeling and multilinear algebraic systems. We expand previous autoregressive techniques to forecast multilinear data, aptly named the L -Transform Tensor autoregressive ( L -TAR for short). Tensor decompositions and multilinear tensor products have allowed for this approach to be a…

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