CP-factorization for high dimensional tensor time series and double projection iterations

arXiv:2606.08560 · stat.ME, econ.EM, stat.ML · Submitted 2026-06-07 · Read on arXiv

stat.ME, econ.EM, stat.ML

Submitted: 2026-06-07

Updated: 2026-09-16

Code: https://github.com/JinyuanChang-Lab/CPTensorTimeSeries

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Consistency — 20× in this paper · explained in 3 episodes
• Sparsity — 6× in this paper · explained in 4 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Robustness — 5× in this paper · explained in 5 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• High-Order Projection Estimator — 3× in this paper
• Theoretical Guarantees — 3× in this paper · explained in 2 episodes
• Tucker Decomposition — 3× in this paper · explained in 2 episodes
• Akaike Information Criterion — 1× in this paper
• Core — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• Robust Tensor Factor Analysis
• HDTSA: An R package for high-dimensional time series analysis
• Positivity of a Hadamard Product

Related papers

• Doubly robust inference via calibration
• Bayesian Empirical Bayes: Simultaneous Inference from Probabilistic Symmetries
• Optimal Watermark Localization in Mixed-Source Large Language Model Texts
• Small area learning
• Flexible Nonparametric Inference for Causal Effects under the Front-Door Model
• A Greedy PDE Router for Blending Neural Operators and Classical Methods