Asymptotics for empirical eigenvalue processes in high-dimensional linear factor models

DOI10.1016/j.jmva.2018.07.001zbMath1409.62125OpenAlexW2827628203WikidataQ129546440 ScholiaQ129546440MaRDI QIDQ1755119

Lajos Horváth, Gregory Rice

Publication date: 4 January 2019

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2018.07.001

zbMATH Keywords

principal component analysischange point analysislinear factor models

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05)

Related Items

Real-time detection of a change-point in a linear expectile model, Wavelet eigenvalue regression in high dimensions, Testing and estimating change-points in the covariance matrix of a high-dimensional time series

Uses Software

• R
• sandwich

Cites Work

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