2 papers
stat.ME2026
High-dimensional Autoregressive Modeling for Time Series with Hierarchical Structures
Lan Li, Shibo Yu, Yingzhou Wang +1
Modern applications have made ubiquitous high-dimensional data, especially time-dependent data, with more and more complicated structures, and it also has become more frequent to e…
stat.ME2025
An Efficient and Interpretable Autoregressive Model for High-Dimensional Tensor-Valued Time Series
Yuxi Cai, Lan Li, Yize Wang +1
In autoregressive modeling for tensor-valued time series, Tucker decomposition, when applied to the coefficient tensor, provides a clear interpretation of supervised factor modelin…