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stat.ME2026
Assumption-Lean Inference for Spectral Differential Network Analysis of High-Dimensional Time Series
Michael Hellstern, Byol Kim, Ali Shojaie
Network analysis for multivariate time series is popular in many fields, from neuroscience to seismology. The inverse spectral density is a common choice for time series network an…
stat.ME2025
Order Selection in Vector Autoregression by Mean Square Information Criterion
Michael Hellstern, Ali Shojaie
Vector autoregressive (VAR) processes are ubiquitously used in economics, finance, and biology. Order selection is an essential step in fitting VAR models. While many order selecti…
stat.ME2024
Spectral Differential Network Analysis for High-Dimensional Time Series
Michael Hellstern, Byol Kim, Zaid Harchaoui +1
Spectral networks derived from multivariate time series data arise in many domains, from brain science to Earth science. Often, it is of interest to study how these networks change…