3 papers
stat.ME2024
SARMA: Scalable Low-Rank High-Dimensional Autoregressive Moving Averages via Tensor Decomposition
Feiqing Huang, Kexin Lu, Yao Zheng
Existing models for high-dimensional time series are overwhelmingly developed within the finite-order vector autoregressive (VAR) framework. However, the more flexible vector autor…
stat.ME2023
Supervised Factor Modeling for High-Dimensional Linear Time Series
Feiqing Huang, Kexin Lu, Guodong Li
Motivated by Tucker tensor decomposition, this paper imposes low-rank structures to the column and row spaces of coefficient matrices in a multivariate infinite-order vector autore…
stat.ME2023
HAR-Ito models and high-dimensional HAR modeling for high-frequency data
Huiling Yuan, Kexin Lu, Yifeng Guo +1
It is an important task to model realized volatilities for high-frequency data in finance and economics and, as arguably the most popular model, the heterogeneous autoregressive (H…