Joint Structural Break Detection and Parameter Estimation in High-Dimensional Nonstationary VAR Models

DOI10.1080/01621459.2020.1770097zbMath1506.62372arXiv1711.07357OpenAlexW3030116412MaRDI QIDQ5881081

Ali Shojaie, Abolfazl Safikhani

Publication date: 9 March 2023

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1711.07357

zbMATH Keywords

structural breakshigh-dimensional time seriestotal variation penaltypiecewise stationarity

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Point estimation (62F10)

Related Items

Scalable change-point and anomaly detection in cross-correlated data with an application to condition monitoring, Forecasting vector autoregressions with mixed roots in the vicinity of unity, The EAS approach for graphical selection consistency in vector autoregression models, Collective Anomaly Detection in High-Dimensional Var Models, A Unified Framework for Change Point Detection in High-Dimensional Linear Models, Graphical models for nonstationary time series, Multiple Change Point Detection in Reduced Rank High Dimensional Vector Autoregressive Models, Likelihood-based analysis in mixture global vars, Detection of Multiple Structural Breaks in Large Covariance Matrices, Inverse covariance operators of multivariate nonstationary time series, Detecting Abrupt Changes in the Presence of Local Fluctuations and Autocorrelated Noise

Uses Software

• bvarsv

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