2022
DOI: 10.48550/arxiv.2205.12201
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Forecasting Multilinear Data via Transform-Based Tensor Autoregression

Abstract: 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 feasible method of fore… Show more

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