2023/04/06 by Jarek Duda, Duda, Jarek · 1 citation
Computer Science · Physics and Astronomy · #Econometrics (econ.EM) #FOS: Computer and information sciences #FOS: Economics and business #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Neural Networks and Applications #Statistical Mechanics and Entropy
paper · pdf · doi:10.48550/arxiv.2304.03069
openalex publication_date 2023/04/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The real life time series are usually nonstationary, bringing a difficult question of model adaptation. Classical approaches like ARMA-ARCH assume arbitrary type of dependence. To avoid their bias, we will focus on recently proposed agnostic philosophy of moving estimator: in time t finding parameters optimizing e.g. Ft=∑_τ