Data-driven shrinkage of the spectral density matrix of a high-dimensional time series

DOI10.1214/14-EJS977zbMath1320.62121MaRDI QIDQ489160

Rainer von Sachs, Mark Fiecas

Publication date: 27 January 2015

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

Full work available at URL: https://projecteuclid.org/euclid.ejs/1421330627

zbMATH Keywords

bootstrapshrinkage estimationspectral analysishigh-dimensional time series

Mathematics Subject Classification ID

Density estimation (62G07) Estimation in multivariate analysis (62H12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Ridge regression; shrinkage estimators (Lasso) (62J07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Inference from stochastic processes and spectral analysis (62M15)

Related Items (8)

Adaptive Bayesian Spectral Analysis of High-Dimensional Nonstationary Time Series ⋮ Time series graphical Lasso and sparse VAR estimation ⋮ Tests for the existence of group effects and interactions for two-way models with dependent errors ⋮ An Algebraic Estimator for Large Spectral Density Matrices ⋮ Change-point detection in panel data via double CUSUM statistic ⋮ Intrinsic Data Depth for Hermitian Positive Definite Matrices ⋮ Spectral analysis of high-dimensional time series ⋮ On the asymptotic distribution of the maximum sample spectral coherence of Gaussian time series in the high dimensional regime

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