Spectral analysis of high-dimensional time series

DOI10.1214/19-EJS1621zbMath1431.62369arXiv1810.11223OpenAlexW2980210171MaRDI QIDQ2326992

Yanyan Li

Publication date: 11 October 2019

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1810.11223

zbMATH Keywords

functional dependencyhigh dimensionsmoothed periodogramfrequency domain time seriessparse precision matrix estimation

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Inference from stochastic processes and spectral analysis (62M15)

Related Items (9)

Adaptive Bayesian Spectral Analysis of High-Dimensional Nonstationary Time Series ⋮ Convergence of covariance and spectral density estimates for high-dimensional locally stationary processes ⋮ Time series graphical Lasso and sparse VAR estimation ⋮ The EAS approach for graphical selection consistency in vector autoregression models ⋮ An Algebraic Estimator for Large Spectral Density Matrices ⋮ Flexible nonlinear inference and change-point testing of high-dimensional spectral density matrices ⋮ Graphical models for nonstationary time series ⋮ Local Whittle estimation of high-dimensional long-run variance and precision matrices ⋮ On the asymptotic distribution of the maximum sample spectral coherence of Gaussian time series in the high dimensional regime

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