Kronecker-structured covariance models for multiway data

作者：Yu Wang, Zeyu Sun, Dogyoon Song, Alfred O. Hero · 发表于：Statistics Surveys · 年份：2022 · DOI：10.1214/22-ss139 · 被引用次数：10 · 研究领域：Tensor decomposition and applications、Computational Physics and Python Applications、Statistical and numerical algorithms

Many applications produce multiway data of exceedingly high dimension. Modeling such multi-way data is important in multichannel signal and video processing where sensors produce multi-indexed data, e.g. over spatial, frequency, and temporal dimensions. We will address the challenges of covariance representation of multiway data and review some of the progress in statistical modeling of multiway covariance over the past two decades, focusing on tensor-valued covariance models and their inference. We will illustrate through a space weather application: predicting the evolution of solar active regions over time.