High-dimensional VAR with low-rank transition

DOI10.1007/s11222-020-09929-7zbMath1448.62130arXiv1905.00959OpenAlexW3101380394MaRDI QIDQ2195856

Karine Bertin, Paul Doukhan, Pierre Alquier, Rémy Garnier

Publication date: 27 August 2020

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1905.00959

zbMATH Keywords

model selectionhigh-dimensional time-series forecastinglow-rank transition matrixvector auto-regressive model (VAR)

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items

Concentration inequalities for non-causal random fields, Tight risk bound for high dimensional time series completion, Extracting a low-dimensional predictable time series, Deviation inequalities for stochastic approximation by averaging, Low-rank matrix estimation via nonconvex optimization methods in multi-response errors-in-variables regression

Uses Software

• CAPUSHE
• GitHub

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