Joint convergence of sample autocovariance matrices when \(p/n\to 0\) with application

DOI10.1214/18-AOS1785zbMath1435.62316OpenAlexW2982482096MaRDI QIDQ2284381

Arup Bose, Monika Bhattacharjee

Publication date: 15 January 2020

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.aos/1572487400

zbMATH Keywords

estimationasymptotic normalitytracemoving average processlimiting spectral distributionsample autocovariance matricestesting of hypothesis

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Hypothesis testing in multivariate analysis (62H15) Inference from stochastic processes and spectral analysis (62M15) Time series analysis of dynamical systems (37M10) Spectral theory; eigenvalue problems on manifolds (58C40)

Related Items (5)

Principal components in linear mixed models with general bulk ⋮ Smallest singular value and limit eigenvalue distribution of a class of non-Hermitian random matrices with statistical application ⋮ Spectral measure of empirical autocovariance matrices of high-dimensional Gaussian stationary processes ⋮ Joint convergence of sample autocovariance matrices when \(p/n\to 0\) with application ⋮ High-dimensional linear models: a random matrix perspective

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