Limiting Spectral Distribution for Large Sample Covariance Matrices withm-Dependent Elements

DOI10.1080/03610920902807929zbMath1193.60042OpenAlexW2134590874MaRDI QIDQ3566542

Jun Hui, Guangming Pan

Publication date: 8 June 2010

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920902807929

zbMATH Keywords

limiting spectral distributionsample covariance matrices\(m\)-dependent

Mathematics Subject Classification ID

Multivariate analysis (62H99) Strong limit theorems (60F15)

Related Items

Limiting Spectral Distribution for Large Sample Covariance Matrices with Graph-Dependent Elements ⋮ Nonparametric estimate of spectral density functions of sample covariance matrices generated by VARMA models ⋮ Marchenko–Pastur law with relaxed independence conditions ⋮ Estimation of the global minimum variance portfolio in high dimensions ⋮ The limiting spectral distribution for large sample covariance matrices with unboundedm-dependent entries

Cites Work

• A central limit theorem for \(m\)-dependent random variables
• DISTRIBUTION OF EIGENVALUES FOR SOME SETS OF RANDOM MATRICES